CLIPS 6.0 User's Guide

May 28, 1993 by Joseph C. Giarratano, Ph.D.

 

  •  
  • Chapter 1
  • Just the Facts
  •  
  • Chapter 2
  • Following the Rules
  •  
  • Chapter 3
  • Adding Details
  •  
  • Chapter 4
  • Variable Interests
  •  
  • Chapter 5
  • Doing It Up In Style
  •  
  • Chapter 6
  • Being Functional
  •  
  • Chapter 7
  • How to Be in Control
  •  
  • Chapter 8
  • Matters of Inheritance
  •  
  • Chapter 9
  • Meaningless Messages
  •  
  • Chapter 10
  • Fascinating Facets
  •  
  • Chapter 11
  • Handling Handlers
  •  
  • Chapter 12
  • Questions and Answers

CLIPS User's Guide

The first step on the road to wisdom is the admission of ignorance. The second step is realizing that you don't have to blab it to the world.

This section was formerly called the Preface, but since nobody read it, I renamed it to a more conventional title that computers users are conditioned to obey. Another suggestion was to call this the Don't Readme section, but since people today believe everything they read, I was afraid they really wouldn't read it.

The purpose of a Preface, oops, excuse me, a Readme, is to provide metaknowledge about the knowledge contained in a book. The term metaknowledge means knowledge about the knowledge. So this description of the Readme is actually metametaknowledge. If you're either confused or intrigued at this point, go ahead and read this book anyway because I need all the readers I can get.

What Is CLIPS?

CLIPS is an expert system tool developed by the Software Technology Branch (STB), NASA/Lyndon B. Johnson Space Center. Since its first release in 1986, CLIPS has undergone continual refinement and improvement. It is now used by thousands of people around the world. The Internet news group comp.ai.shells often has discussions of CLIPS. NASA supports CLIPS and other software products developed by the STB through the STB Bulletin Board (please see back of this book for more details.)

CLIPS is designed to facilitate the development of software to model human knowledge or expertise.

There are three ways to represent knowledge in CLIPS:

_ Rules, which are primarily intended for heuristic knowledge based on experience.

_ Deffunctions and generic functions, which are primarily intended for procedural knowledge.

_ Object-oriented programming, also primarily intended for procedural knowledge. The five generally accepted features of object-oriented programming are supported: classes, message-handlers, abstraction, encapsulation, inheritance, polymorphism. Rules may pattern match on objects and facts.

You can develop software using only rules, only objects, or a mixture of objects and rules.

CLIPS has also been designed for full integration with other languages such as C and Ada. In fact, CLIPS is an acronym for C Language Integrated Production System. Rules and objects form an integrated system too since rules can pattern-match on facts and objects. In addition to being used as a stand-alone tool, CLIPS can be called from a procedural language, perform its function, and then return control back to the calling program. Likewise, procedural code can be defined as external functions and called from CLIPS. When the external code completes execution, control returns to CLIPS.

If you are already familiar with object-oriented programming in other languages such as C++, Smalltalk, Object C, or Turbo Pascal, you know the advantages of objects in developing software. If you are not familiar with object-oriented programming, you will find that CLIPS is an excellent tool for learning this new concept in software development.

What This Book is About

The CLIPS User's Guide is an introductory tutorial on the basic features of CLIPS. It is not intended to be a comprehensive discussion of the entire tool. The companion volume to this book is theCLIPS Reference Manual., which does provide a complete, comprehensive discussion of all the topics in this book and much more.

Who Should Read This Book

The purpose of the CLIPS User's Guide is to provide an easy to read, elementary introduction to expert systems for people with little or no experience with expert sys tems.

The CLIPS User's Guide can be used in the classroom or for self-teaching. The only prerequisite is that you have a basic knowledge of programming in a high-level language such as Pascal, Ada, FORTRAN, C (OK, BASIC if nothing else, but we won't admit it in public and will disavow this statement if asked.)

How To Use This Book

The CLIPS User's Guide is designed for people who want a quick introduction to expert system programming in a hands-on manner. The examples are of a very general nature. Also, since learning a new language can be a frustrating experience, the writing is in a light, humorous style (I hope) compared to serious-minded, massive, and intimidating college textbooks. Hopefully, the humor will not offend anyone with a sense of humor.

For maximum benefit, you should type in the example programs in the text as you read through the book. By typing in the examples, you will see how the programs should work and what error messages occur if you make a mistake. The output for the examples is shown or described after each example. Finally, you should read the corresponding material in the CLIPS Reference Manual as you cover each chapter in the CLIPS User's Guide..

Like any other programming language, you will only learn programming in CLIPS by writing programs in it. To really learn expert system programming, you should pick a problem of interest and write it in CLIPS.

Acknowledgments

I greatly appreciate the advice and reviews of this book by many people. Thanks to Gary Riley, Chris Culbert, Brian Donnell, Bryan Dulock, Steven Lewis, Ann Baker, Steve Mueller, Stephen Baudendistel, Yen Huynh, Ted Leibfried, Robert Allen, Jim Wescott, Marsha Renals, Pratibha Boloor, Terry Feagin, and Jack Aldridge. Special thanks to Bob Savely for supporting the development of CLIPS.

Chapter 1 Just the Facts

If you ignore the facts, you'll never worry about being wrong

This chapter introduces the basic concepts of an expert system. You'll see how to insert and remove facts in CLIPS. If you are using a Macintosh or the Windows version of CLIPS for the IBM PC (or compatible), you can select most commands by the mouse instead of typing them in. The arrow keys on the keyboard will also move the cursor and allow selection of menu items.

Introduction

CLIPS is a type of computer language designed for writing applications called expert systems. An expert system is a program which is specifically intended to model human expertise or knowledge. In contrast, common programs such as payroll programs, word processors, spreadsheets, computer games, and so forth, are not intended to embody human expertise or knowledge. (One definition of an expert is someone more than 50 miles from home and carrying a briefcase.)

CLIPS is called an expert system tool because it is a complete environment for developing expert systems which includes features such as an integrated editor and a debugging tool. The word shell is reserved for that portion of CLIPS which performs inferences or reasoning. The CLIPS shell provides the basic elements of an expert system:

1. fact-list, and instance-list: Global memory for data

2. knowledge-base: Contains all the rules, the rule-base

3. inference engine: Controls overall execution of rules

A program written in CLIPS may consist of rules, facts, and objects. The inference engine decides which rules should be executed and when. A rule- based expert system written in CLIPS is a data-driven program where the facts, and objects if desired, are the data that stimulate execution via the inference engine.

This is one example of how CLIPS differs from procedural languages such as Pascal, Ada, BASIC, FORTRAN, and C. In procedural languages, execution can proceed without data. That is, the statements are sufficient in those languages to cause execution. For example, a statement such as PRINT 2 + 2 could be immediately executed in BASIC. This is a complete statement that does not require any additional data to cause its execution. However, in CLIPS, data are required to cause the execution of rules.

Originally, CLIPS had capabilities to represent only rules and facts. However, the enhancements of Version 6.0 allow rules to match objects as well as facts. Also, objects may be used without rules by sending messages and so the inference engine is no longer necessary if you use only objects. In chapters 1 through 7, we'll discuss the facts and rules of CLIPS. The object features of CLIPS are covered in chapters 8 through 12.

The Beginning and the End

To begin CLIPS, just enter the appropriate run command for your system. You should see the CLIPS prompt appear as follows:

CLIPS>

At this point, you can start entering commands directly into CLIPS. The mode in which you are entering direct commands is called the top-level. If you have a window version of CLIPS, you can just select the command using the mouse or arrow keys rather than typing it in. Please refer to the CLIPS Reference Manual for a discussion of the commands supported under windows. For simplicity and uniformity in this book, we'll assume the commands are typed in.

The normal mode of leaving CLIPS is with the exit command. Just type

(exit)

in response to the CLIPS prompt and then press the carriage return key.

Making a List

As with other programming languages, CLIPS recognizes certain keywords. For example, if you want to put data in the fact-list, you can use the assert command.

As an example of assert, enter the following right after the CLIPS prompt as shown:

CLIPS> (assert (duck))

Here the assert command takes (duck) as its argument. Be sure to always press the carriage return key to send the line to CLIPS.

You will see the response

<Fact-0>

which indicates CLIPS has stored the duck fact in the fact-list and given it the identifier 0. The angle-brackets are used as a delimiter in CLIPS to surround the name of an item. CLIPS will automatically name facts using a sequentially increasing number and list the highest fact-index when one or more facts is asserted.

Notice that the (assert) command and its (duck) argument are surrounded by parentheses. Like many other expert system languages, CLIPS has a LISP-like syntax which uses parentheses as delimiters. Although CLIPS is not written in LISP, the style of LISP has influenced the development of CLIPS.

And Checking It Twice

Suppose you want to see what's in the fact-list. If your version of CLIPS supports windows, you may just select the appropriate command from the menu. Alternatively, you can enter commands from the keyboard. In the following, we'll describe the keyboard commands since the window selections are self-explanatory.

The keyboard command to see facts is with the facts command. Enter (facts) in response to the CLIPS prompt and CLIPS will respond with a list of facts in the fact-list. Be sure to put parentheses around the command or CLIPS will not accept it. The result of the (facts) command in this example should be

CLIPS> (facts)

f-0 (duck)

For a total of 1 fact.

CLIPS>

The term f-0 is the fact identifier assigned to the fact by CLIPS. Every fact inserted into the fact-list is assigned a unique fact identifier starting with the letter "f" and followed by an integer called the fact-index. On starting up CLIPS, and after certain commands such as clear and reset (to be discussed in more detail later), the fact-index will be set to zero, and then incremented by one as each new fact is asserted. The (reset) command will also insert a fact (initial-fact) as f-0. This fact is often used for convenience to initially activate rules. Shown following is what happens when a (reset) is done first.

CLIPS> (reset)

CLIPS& gt; (facts)

f-0 (initial-fact)

For a total of 1 fact.

CLIPS> (assert (duck))

<Fact-1>

CLIPS> (facts)

f-0 (initial-fact)

f-1 (duck)

For a total of 2 facts.

CLIPS>

Notice that the fact-index is <Fact-1> after the duck fact is asserted because there are now two facts in working memory and the duck has index 1.

What happens if you try to put a second duck into the fact-list? Let's try it and see. Assert a new (duck), then issue a (facts) command as follows

CLIPS> (assert (duck))

FALSE

CLIPS> (facts)

f-0 (initial-fact)

f-1 (duck)

For a total of 2 facts.

CLIPS>

The FALSE message is returned by CLIPS to indicate that it was not possible to perform this command. You'll see just the original "f-1 (duck)". This shows that CLIPS will not accept a duplicate entry of a fact. However, there is an override command, setfact-duplication, which will allow duplicate fact entry.

Of course you can put in other, different facts. For example, assert a (quack) fact and then issue a (facts) command. You'll see

CLIPS> (assert (quack))

<Fact-2>

CLIPS> (facts)

f-0 (initial-fact)

f-1 (duck)

f-2 (quack)

For a total of 3 facts.

CLIPS>

Notice that the (quack) fact is now in the fact-list.

Facts may be removed or retracted. When a fact is retracted, the other facts do not have their indices changed, and so there may be "missing" fact-indices. As an analogy, when a football player leaves a team and is not replaced, the jersey numbers of the other players are not all adjusted because of the missing number (unless they really hate the guy's guts and want to forget he ever played for them.)

Clearing Up the Facts

The clear command removes all facts from memory, as shown by the following.

CLIPS> (facts)

f-0 (initial-fact)

f-1 (duck)

f-2 (quack)

For a total of 3 facts.

CLIPS> (clear)

CLIPS>

and all facts in the fact-list will be removed.

The (clear) command essentially restores CLIPS to its original startup state. It clears the memory of CLIPS and resets the fact-identifier to zero. To see this, assert (animal-is duck), then check the fact-list. Notice that (animal-is duck) has a fact-identifier of f-0 because the (clear) command reset the fact identifiers. The (clear) command actually does more than just remove facts. Besides removing all the facts, (clear) also removes all the rules, as you'll see in the next chapter.

The following example shows how three facts are asserted, and the (facts) command is used. The (clear) command is used to get rid of all facts in memory and reset the fact-indices to start with f-0.

CLIPS> (clear)

CLIPS> (assert (a) (b) (c))

<Fact-2>

CLIPS> (facts)

f-0 (a)

f-1 (b)

f-2 (c)

For a total of 3 facts.

CLIPS> (facts 0)

f-0 (a)

f-1 (b)

f-2 (c)

For a total of 3 facts.

CLIPS> (facts 1)

f-1 (b)

f-2 (c)

For a total of 2 facts.

CLIPS> (facts 2)

f-2 (c)

For a total of 1 fact.

CLIPS> (facts 0 1)

f-0 (a)

f-1 (b)

For a total of 2 facts.

CLIPS> (facts 0 2 2)

f-0 (a)

f-1 (b)

For a total of 2 facts.

CLIPS>

Notice only one (assert) is used to assert the three facts, (a), (b), and (c). The highest fact-index is 2 and this is returned by CLIPS in the informational message <Fact- 2>. The much longer alternative would be to assert one fact per command (This may be done by people who like to show off their typing speed.)

Sensitive Fields and Slurping

A fact such as (duck) or (quack) is said to consist of a single field. A field is a placeholder (named or unnamed) that may have a value associated with it. As a simple analogy, you can think of a field as a picture frame. The frame can hold a picture, perhaps a picture of your pet duck (For those of you who are curious what a picture of a "quack" looks like, it could be (1) a photo of an oscilloscope trace of a duck saying "quack", where the signal input comes from a microphone, or (2) for those of you who are more scientifically inclined, a Fast Fourier Transform of the "quack" signal, or (3) a TV-huckster selling a miracle cure for wrinkles, losing weight, etc.). Named placeholders are only used with deftemplates, described in more detail in chapter 5.

The (duck) fact has a single, unnamed placeholder for the value duck. This is an example of a single-field fact. A field is a placeholer for a value. As an analogy to fields, think of dishes (fields) for holding food (values).

The order of unnamed fields is significant. For example, if a fact was defined

(Brian duck)

and interpreted by a rule as the hunter Brian shot a duck, then the fact

(duck Brian)

would mean that the hunter duck shot a Brian. In contrast, the order of named fields is not significant, as you'll see later with deftemplate.

Actually, it is good software engineering to start the fact with a relation that describes the fields. A better fact would be

(hunter-game duck Brian)

to imply that the first field is the hunter and the second field is the game.

A few definitions are now necessary. A list is a group of items with no implied order. Saying that a list is ordered means that the position in the list is significant. A multifield is a sequence of fields, each of which may have a value. The examples of (duck Brian) and (Brian duck) are multifield facts. If a field has no value, the special symbol nil, which means "nothing" may be used for an empty field as a placeholder. For example,

(duck nil)

would mean that the killer duck bagged no trophies today.

Note that the nil is necessary to indicate a placeholder, even if it has no value. For example, think of a field as analogous to a mailbox. There's a big difference between an empty mailbox, and no mailbox at all. Without the nil, the fact becomes a single-field fact (duck). If a rule depends on two fields, it will not work with only one field, as you'll see later.

There are a number of different types of fields available: float, integer, symbol, string, externaladdress, factaddress, instancename and instanceaddress The type of each field is determined by the type of value stored in the field. In an unnamed field, the type is determined implicitly by what type you put in the field. In deftemplates, you can explicitlty declare the type of value that a field can contain. The use of explicit types enforces the concepts of software engineering, which is a discipline of programming to produce quality software.

A symbol is one type of field that starts with a printable ASCII character and is followed optionally by zero or more printable characters. Fields are commonly delimited or bounded, by one or more spaces or parentheses. For example,

(duck-shot Brian Gary Rey)

has four fields to indicate all the hunters shot by the killer duck. In this fact, the fields are delimited by spaces, and the opening and closing parentheses.

Facts are not allowed to be embedded within other facts. For example, the following is an illegal ordered fact.

(duck (shot Brian Gary Rey))

However, this could be a legal defte mplate fact if "shot" is defined as the name of a field, while "Brian Gary Rey" are the values associated with the named field.

CLIPS is case-sensitive. Also, certain characters have special meaning to CLIPS.

" ( ) & | < ~ ; ? $

The "&", "|", and "~" may not be used as stand-alone symbols or as any part of a symbol.

Some characters act as delimiters by ending a symbol. The following characters act as delimiters for symbols.

_ any non-printable ASCII character, including spaces, carriage returns, tabs, and linefeeds

_ double quotes, "

_ opening and closing parentheses, ()

_ ampersand, &

_ vertical bar, |

_ less than, <. Note that this may be the first character of a symbol

_ tilde, ~

_ semicolon, ; indicates start of a comment, a carriage return ends it

_ ? and $? may not begin a symbol but may be inside it

The semicolon acts as the start of a comment in CLIPS. If you try to assert a semicolon, CLIPS will think you're entering a comment and wait for you to finish. If you accidentally enter a semicolon in top-level, just type in a closing parenthesis and carriage return. CLIPS will respond with an error message and the CLIPS prompt will reappear (This is one of the few approved occasions in life in which it's necessary to do something wrong to get something right.)

As you read through this manual, you will learn the special meanings of the characters above. With the exception of the "&", "|", and "~", you may use the others as described. However, it may be confusing to someone reading your program and trying to understand what the program is doing. In general, it's best to avoid using these characters in symbols unless you have some good reason for using them.

The following are examples of symbols.

duck

duck1

duck_soup

duck-soup

duck1-1_soup-soup

d!?#%^

The second type of field is the string. A string must begin and end with double quotes. The double quotes are part of the field. Zero or more characters of any kind can appear between the double quotes. Some examples of strings follow.

"duck"

"duck1"

"duck/soup"

"duck soup"

"duck soup is good!!!"

The third and fourth types of field are numeric fields. A field which represents a number which can be either an integer or floatingpoint type field. A floating-point type is commonly referred to simply as a float.

All numbers in CLIPS are treated as long integers or double-precision floats. Numbers without a decimal point are treated as integers unless they are outside integer range. The range is machine dependent on the number of bits, N, used to represent the integer as follows.

- 2N-1 ... 2N-1-1

For 32-bit long integers, this corresponds to a range of numbers

- 2,147,483,648 ... 2,147,483,647

As some examples of numbers, assert the following data where the last number is in exponential notation, and uses the "e" or "E" for the power-of-ten.

CLIPS> (facts)

CLIPS> (clear)

CLIPS> (assert (number 1))

<Fact-0>

CLIPS> (assert (x 1.5))

<Fact-1>

CLIPS> (assert (y -1))

<Fact-2>

CLIPS> (assert (z 65))

<Fact-3>

CLIPS> (assert (distance 3.5e5))

<Fact-4>

CLIPS> (assert (coordinates 1 2 3))

<Fact-5>

CLIPS> (assert (coordinates 1 3 2))

<Fact-6>

CLIPS> (facts)

f-0 (number 1)

f-1 (x 1.5)

f-2 (y -1)

f-3 (z 65)

f-4 (distance 350000.0)

f-5 (coordinates 1 2 3)

< /tt>

 

f-6 (coordinates 1 3 2)

For a total of 7 facts.

CLIPS>

As you can see, CLIPS prints the number entered in exponential notation as 350000.0 because it converts from power-of-ten format to floating-point if the number is small enough.

Notice that each number must start with a symbol such as "number", "x", "y", etc. Before CLIPS version 6.0, it was possible to enter only a number as a fact. However, now a symbol is required as the first field. Also, certain reserved words used by CLIPS cannot be used as the first field, but may be used as others. For example, the names of predefined CLIPS functions (see Appendix I of the CLIPS Reference Manual), def-constructs, and so forth cannot be used.

A fact consists of one or more fields enclosed in matching left and right parentheses. For simplicity we'll only discusss facts in the first seven chapters, but most of the discussion of pattern matching applies to objects as well. Exceptions are certain functions such as assert and retract which only apply to facts, not objects. The corresponding ways to handle objects are discussed in chapters 8-12.

A fact may be ordered or unordered. All the examples you've seen so far are ordered facts because the order of fields makes a difference. For example, notice that CLIPS considers these as separate facts although the same values "1", "2", and "3" are used in each.

f-5 (coordinates 1 2 3)

f-6 (coordinates 1 3 2)

Ordered facts must use field position to define data. As an example, the ordered fact (duck Brian) has two fields and so does (Brian duck). However, these are considered as two separate facts by CLIPS because the order of field values is different. In contrast, the fact (duck-Brian) has only one field because of the "-" concatenating the two values.

Deftemplate facts, described in more detail later, are unordered because they use named fields to define data. This is analogous to the use of records in Pascal and other languages.

Multiple fields normally are separated by white space consisting of one or more spaces, tabs, carriage returns, or linefeeds. For example, enter the following examples as shown and you'll see that each stored fact is the same.

CLIPS> (clear)

CLIPS> (assert (The duck says "Quack."))

<Fact-0>

CLIPS> (facts)

f-0 (The duck says "Quack.")

For a total of 1 fact.

CLIPS> (clear)

CLIPS> (assert (The duck says "Quack." ))

<Fact-0>

CLIPS> (facts)

f-0 (The duck says "Quack.")

For a total of 1 fact.

CLIPS>

Carriage returns may also be used to improve readability. In the following example, a carriage return is typed after every field and the asserted fact is the same as before when the fact was entered on one line.

CLIPS> (clear)

CLIPS> (assert (The

duck

says

"Quack"))

<Fact-0>

CLIPS> (facts)

f-0 (The duck says "Quack")

For a total of 1 fact.

CLIPS>

However, be careful if you insert a carriage return inside of a string, as the following example shows.

CLIPS> (assert (The

duck

says

"Quack

"))

<Fact-1>

CLIPS> (facts)

f-0 (The duck says "Quack")

f-1 (The duck says "Quack

")

For a total of 2 facts.

CLIPS>

As you can see, the carriage return embedded in the double quotes was output with the string to put the closing double quote on the next line. This is important because CLIPS considers fact f-0 as distinct from fact f-1.

Notice also that CLIPS preserved the uppercase and lowercase letters in the fields of the fact. That is, the "T" of "The" and the "Q" of "Quack" are uppercase. CLIPS is said to be case-sensitive because it distinguishes between uppercase and lowercase letters. For example, assert the facts (duck) and (Duck) and then issue a (facts) command. You'll see that CLIPS allows you to assert (duck) and (Duck) as different facts because CLIPS is case-sensitive.

The following example is a more realistic case in which carriage returns are used to improve the readability of a list. To see this, assert the following fact where carriage returns and spaces are used to put fields at appropriate places on different lines. Dashes or minus signs are used intentionally to create single fields, so CLIPS will treat items like "fudge sauce" as a single field.

CLIPS> (clear)

CLIPS> (assert (grocery-list

ice-cream

cookies

candy

fudge-sauce))

<Fact-0>

CLIPS> (facts)

f-0 (grocery-list ice-cream cookies candy fudge-sauce)

For a total of 1 fact.

CLIPS>

As you can see, CLIPS replaced the carriage returns and tabs with single spaces. While the use of white space in separating the facts is convenient for a person reading a program, they are converted to single spaces by CLIPS.

A Matter of Style

It is good rule-based programming style to use the first field of a fact to describe the relationship of the following fields. When used this way, the first field is called a relation. The remaining fields of the fact are used for specific values. An example is (grocery-list ice-cream cookies candy fudge-sauce). The dashes are used to make multiple words fit in a single field.

Good documentation is even more important in an expert system than in languages such as Pascal, C, Ada, etc., because the rules of an expert system are not generally executed in a sequential manner. CLIPS aids the programmer in writing descriptive facts like this by means of deftemplates.

Another example of related facts is (duck), (horse), and (cow). It's better style to refer to them as

(animal-is duck)

(animal-is horse)

(animal-is cow)

or as the single fact

(animals duck horse cow)

since the relation animal-is or animals describes their relation and so provides some documentation to the person reading the code.

The explicit relations, animal-is and animals, make more sense to a person than the implicit meaning of (duck), (horse), and (cow). While this example is simple enough that anyone can figure out the implicit relations, it is an easy trap to fall into to write facts in which the relationship is not so obvious (In fact, it's much easier to make something more complicated than easy, since people are more impressed by complexity than simplicity.)

Getting Spaced Out

Since spaces are used to separate multiple fields, it follows that spaces cannot simply be included in facts. For example,

CLIPS> (clear)

CLIPS> (assert (animal-is walrus))

<Fact-0>

CLIPS> (assert ( animal-is walrus ))

FALSE

CLIPS> (assert ( animal-is walrus ))

FALSE

CLIPS> (facts)

f-0 (animal-is walrus)

For a total of 1 fact.

CLIPS>

Only one fact, (animal-is walrus), is asserted since CLIPS ignores white space and considers all these facts equivalent. Thus, CLIPS responds with a FALSE when you try to enter the last two duplicate facts. CLIPS normally does not allow duplicate facts to be entered unless you change the set-fact-duplicate setting.

If you want to include spaces in a fact, you must use double quotes. For example,

CLIPS> (clear)

CLIPS> (assert (animal-i s "duck"))

<Fact-0>

CLIPS> (assert (animal-is "duck "))

<Fact-1>

CLIPS> (assert (animal-is " duck"))

<Fact-2>

CLIPS> (assert (animal-is " duck "))

<Fact-3>

CLIPS> (facts)

f-0 (animal-is "duck")

f-1 (animal-is "duck ")

f-2 (animal-is " duck")

f-3 (animal-is " duck ")

For a total of 4 facts.

CLIPS>

Note that the spaces make each of these facts different to CLIPS although the meaning is the same to a person.

What if you want to include the double quotes in a field? The correct way to put double quotes in a fact is with the backslash, "", as the following example shows.

CLIPS> (clear)

CLIPS> (assert (single-quote "duck"))

<Fact-0>

CLIPS> (assert (double-quote "\"duck\""))

<Fact-1>

CLIPS> (facts)

f-0 (single-quote "duck")

f-1 (double-quote ""duck"")

For a total of 2 facts.

CLIPS>

Retract that Fact

Now that you know how to put facts into the fact-list, it's time to learn how to remove them. Removing facts from the fact-list is called retraction and is done with the retract command. To retract a fact, you must specify the fact index of the fact as the argument of retract. For example, set up your fact-list as follows.

CLIPS> (clear)

CLIPS> (assert (animal-is duck))

<Fact-0>

CLIPS> (assert (animal-sound quack))

<Fact-1>

CLIPS> (assert (The duck says "Quack."))

<Fact-2>

CLIPS> (facts)

f-0 (animal-is duck)

f-1 (animal-sound quack)

f-2 (The duck says "Quack.")

For a total of 3 facts.

CLIPS>

To remove the last fact with index f-2, enter the retract command and then check your facts as follows.

CLIPS> (retract 2)

CLIPS> (facts)

f-0 (animal-is duck)

f-1 (animal-sound quack)

For a total of 2 facts.

CLIPS>

What happens if you try to retract a fact that's already retracted, or a non-existent fact? Let's try it and see.

CLIPS> (retract 2)

[PRNTUTIL1] Unable to find fact f-2.

CLIPS>

Notice that CLIPS issues an error message if you try to retract a non-existent fact. The moral of this is that you can't take back what you haven't given.

Now let's retract the other facts as follows.

CLIPS> (retract 1)

CLIPS> (facts)

f-0 (animal-is duck)

For a total of 1 fact.

CLIPS> (retract 0)

CLIPS> (facts)

CLIPS>

To retract a fact, you must specify the fact-index.

You can also retract multiple facts at once, as shown by the following.

CLIPS> (clear)

CLIPS> (assert (animal-is duck))

<Fact-0>

CLIPS> (assert (animal-sound quack))

<Fact-1>

CLIPS> (assert (The duck says "Quack."))

<Fact-2>

CLIPS> (retract 0 2)

CLIPS> (facts)

f-1 (animal-sound quack)

For a total of 1 fact.

CLIPS>

To retract multiple facts, just list the fact-id numbers in the (retract) command.

You can just use (retract *) to retract all the facts, where the "*" indicates all .

CLIPS> (clear)

CLIPS> (assert (animal-is duck))

<Fact-0>

CLIPS> (assert (animal-sound quack))

<Fact-1>

CLIPS> (assert (The d uck says "Quack."))

<Fact-2>

CLIPS> (facts)

f-0 (animal-is duck)

f-1 (animal-sound quack)

f-2 (The duck says "Quack.")

For a total of 3 facts.

CLIPS> (retract *)

CLIPS>

Watch that Fact

CLIPS provides several commands to help you debug programs. One command allows you to continuously watch facts being asserted and retracted. This is more convenient than having to type in a (facts) command over and over again and trying to figure out what's changed in the fact-list.

To start watching facts, enter the command (watch facts) as shown in the following example.

CLIPS> (clear)

CLIPS> (watch facts)

CLIPS> (assert (animal-is duck))

==> f-0 (animal-is duck)

<Fact-0>

CLIPS>

The right double arrow symbol, ==>, means that a fact is entering memory while the left double arrow indicates a fact is leaving memory, as shown following.

CLIPS> (reset)

<== f-0 (animal-is duck)

==> f-0 (initial-fact)

CLIPS> (assert (animal-is duck))

==> f-1 (animal-is duck)

<Fact-1>

CLIPS> (retract 1)

<== f-1 (animal-is duck)

CLIPS> (facts)

f-0 (initial-fact)

For a total of 1 fact.

CLIPS>

The (watch facts) command provides a record that shows the dynamic or changing state of the fact-list. In contrast, the (facts) command show the static state of the fact- list since it displays the current contents of the fact-list. To turn off watching facts, enter (unwatch facts).

There are a number of things you can watch. These include the following, which are described in more detail in the CLIPS Reference Manual. The comment in CLIPS begins with a semicolon. Everything after the semicolon is ignored by CLIPS.

(watch facts)

(watch instances) ; used with objects

(watch slots) ; used with objects

(watch rules)

(watch activations)

(watch messages) ; used with objects

(watch message-handlers) ; used with objects

(watch generic-functions)

(watch methods) ; used with objects

(watch deffunctions)

(watch compilations) ; on by default

(watch statistics)

(watch globals)

(watch focus)

(watch all) ; watch everything

As you use more of the capabilities of CLIPS, you'll find these (watch) commands very helpful in debugging. To turn off a (watch) command, enter an unwatch command. For example, to turn of watching compilations, enter (unwatch compilations).

With a Little Help

CLIPS has on-line help available. To access the help feature, just enter (help)

and press the carriage return key. In a short while, you'll see a menu of topics. For more information on using (help), read the help section on HELP_USAGE. To exit from help, keep pressing the carriage return key until the CLIPS prompt reappears. If an error message appears that says CLIPS could not find the help file, clips.hlp, you can find out where CLIPS expected it to be by using the command (help-path).

Chapter 2 Following the Rules

If you want to get anywhere in life, don't break the rules
-- make the rules!

In the previous chapter, you learned about facts. Now you'll see how the rules of an expert system utilize facts in making a program execute.

Making Good Rules

To accomplish useful work, an expert system must have rules as well as facts. Since you've seen how facts are asserted and retracted, it's time to see how rules work. A rule is similar to an IF THEN statement in a procedural language like Ada, C, or Pascal. An IF THEN rule can be expressed in a mixture of natural language and computer language as follows:

IF certain conditions are true

THEN execute the following actions

Another term for the above statement is pseudocode, which literally means false code. While pseudocode cannot be directly executed by the computer, it serves as a very useful guide to writing executable code. Pseudocode is also helpful in documenting rules. A translation of rules from natural language to CLIPS is not very difficult if you keep this IF THEN analogy in mind. As your experience with CLIPS grows, you'll find that writing rules in CLIPS becomes easy. You can either type rules directly into CLIPS or load rules in from a file of rules created by a text editor.

The pseudocode for a rule about duck sounds might be

IF the animal is a duck

THEN the sound made is quack

The following is a fact, and a rule named duck which is the pseudocode above expressed in CLIPS syntax. The name of the rule follows immediately after the keyword defrule. Although you can enter a rule on a single line, it's customary to put different parts on separate lines to aid readability and editing.

CLIPS> (clear)

CLIPS> (assert (animal-is duck))

<Fact-0>

CLIPS> (defrule duck

(animal-is duck)

=>

(assert (sound-is quack)))

CLIPS>

If you type in the rule correctly as shown, you should see the CLIPS prompt reappear. Otherwise, you'll see an error message. If you get an error message, it is likely that you misspelled a keyword or left out a parenthesis. Remember, the number of left and right parentheses always must match in a statement.

The same rule is shown following with comments added to match the parts of the rule. Also shown is the optional rule-header comment in quotes, "Here comes the quack". There can be only one rule-header comment and it must be placed after the rule name and before the first pattern. Although we're only discussing pattern matching against facts now, more generally a pattern can be matched against a pattern entity. A pattern entity is either a fact or an instance of a user-defined class. Pattern matching on objects will be discussed later.

CLIPS tries to match the pattern of the rule against a pattern entity. Of course, white space consisting of spaces, tabs, and carriage returns may be used to separate the elements of a rule to improve readability. Other comments begin with a semicolon and continue until the carriage return key is pressed to terminate a line. Comments are ignored by CLIPS.

(defrule duck "Here comes the quack" ; Rule header

(animal-is duck) ; Pattern

=> ; THEN arrow

(assert (sound-is quack))) ; Action

_ Only one rule name can exist at one time in CLIPS.

Entering the same rule name, in this case "duck", will replace any existing rule with that name. That is, while there can be many rules in CLIPS, there can be only one rule which is named "duck". This is analogous to other programming languages in which only one procedure name can be used to uniquely identify a procedure.

The general syntax of a rule is shown following.

(defrule rule_name "optional_comment"

(pattern_1) ; Left-Hand Side (LHS)

(pattern_2) ; of the rule consisting of elements

. ; before the "=>"

.

.

(pattern_N)

=>

(action_1) ; Right-Hand Side (RHS)

(action_2) ; of the rule consisting of elements

. ; after the "=>"

.

(action_M)) ; the last ")" balances the opening ; "(" to the left of "defrule". Be

; sure all your parentheses balance ; or you will get error messages

The entire rule must be surrounded by parentheses. Each of the rule patterns and actions must be surrounded by parentheses. An action is actually a function which typically has no return value, but performs some useful action, such as an (assert) or (retract). For example, an action might be (assert (duck)). Here the function name is "assert" and its argument is "duck". Notice that we don't want any return value such as a number. Instead, we want the fact (duck) to be asserted. A function in CLIPS is a piece of executable code identified by a specific name, which returns a useful value or performs a useful side-effect, such as (printout).

A rule often has multiple patterns and actions. The number of patterns and actions do not have to be equal, which is why different indices, N and M, were chosen for the rule patterns and actions.

Zero or more patterns may be written after the rule header. Each pattern consists of one or more fields. In the duck rule, the pattern is (animal-is duck), where the fields are "animal-is" and "duck". CLIPS attempts to match the patterns of rules against facts in the fact-list. If all the patterns of a rule match facts, the rule is activated and put on the agenda. The agenda is a collection of activations which are those rules which match pattern entities. Zero or more activations may be on the agenda.

The symbol "=>" that follows the patterns in a rule is called an arrow. The arrow represents the beginning of the THEN part of an IF-THEN rule (and may be read as "implies").

The last part of a rule is the list of zero or more actions that will be executed when the rule fires. In our example, the one action is to assert the fact (sound-is quack). The term fires means that CLIPS has selected a certain rule for execution from the agenda.

_ A program will cease execution when no activations are on the agenda.

When multiple activations are on the agenda, CLIPS automatically determines which activation is appropriate to fire. CLIPS orders the activations on the agenda in terms of increasing priority or salience.

The part of the rule before the arrow is called the left-hand side (LHS) and the part of the rule after the arrow is called the right-hand side (RHS). If you enter a (reset) command, CLIPS memory is cleared and the special fact (initial- fact) is always put into the fact-list with fact-identifier "f-0". If no patterns are specified, the pattern (initial-fact) is used for the LHS.

Let's Get Quacking

CLIPS always executes the actions on the RHS of the highest priority rule on the agenda. This rule is then removed from the agenda and the actions of the new highest salience rule is executed. This process continues until there are no more activations or a command to stop is encountered.

You can check what's on the agenda with the agenda command. For example,

CLIPS> (agenda)

0 duck: f-0

For a total of 1 activation.

CLIPS>

The first number "0" is the salience of the "duck" activation, and "f-0" is the fact-identifier of the fact, (animal-is duck), which matches the activation. If the salience of a rule is not declared explicitly, CLIPS assigns it the default value of zero, where the possible salience values range from -10,000 to 10,000. In this book, we'll use the definition of the term default as meaning the standard way.

If there is only one rule on the agenda, that rule will fire. Since the LHS pattern of the duck-sound rule is

(animal-is duck)

this pattern will be satisfied by the fact (animal-is duck) and so the duck-sound rule should fire.

Each field of the pattern is said to be a literal constraint. The term literal means having a constant value, as opposed to a variable whose value is expected to change. In this case, the literals are "animal-is" and "duck".

To make a program run, just enter the run command. Type (run) and press the carriage return key. Then do a (facts) to check that the fact was asserted by the rule.

CLIPS> (run)

CLIPS> (facts)

f-0 (animal-is duck)

f-1 (sound-is quack)

For a total of 2 facts.

CLIPS>

Before going on, let's save the duck rule with the save command so that you don't have to type it in again (if you haven't already saved it in an editor). Just enter a command such as

(save "duck.clp")

to save the rule from CLIPS memory to disk and name the file "duck.clp" where the ".clp" is simply a convenient extension to remind us this is a CLIPS source code file. Note that saving the code from CLIPS memory like this will only preserve the optional rule-header comment in quotes and not any semicolon comments.

Kick your Duck

An interesting question may occur to you at this time. What if you (run) again? There is a rule and a fact which satisfies the rule, so the rule should fire. However, if you try this and (run) again, you'll see that the rule won't fire. This may be somewhat frustrating. However, before you do something drastic to ease your frustration -- like kicking your pet duck -- you need to know a little more about some basic principles of expert systems.

A rule is activated if its patterns are matched by a

1. a brand new pattern entity that did not exist before or,

2. a pattern entity that did exist before but was retracted and reasserted, i.e., a "clone" of the old pattern entity, and thus now a new pattern entity.

The rule, and indices of the matching patterns, is the activation. If either the rule or the pattern entity, or both change, the activation is removed. An activation may also be removed by a command or an action of another rule that fired before and removed the conditions necessary for activation.

The Inference Engine sorts the activations according to their salience. This sorting process is called conflict resolution because it eliminates the conflict of deciding which rule should fired next. CLIPS executes the RHS of the rule with the highest salience on the agenda, and removes the activation. This execution is called firing the rule in analogy with the firing of a neuron. A neuron emits a voltage pulse when an appropriate stimulus is applied. After a neuron fires, it undergoes refraction and cannot fire again for a certain period of time. Without refraction, neurons would just keep firing over and over again on exactly the same stimulus.

Without refraction, expert systems always would be caught in trivial loops. That is, as soon as a rule fired, it would keep firing on that same fact over and over again. In the real world, the stimulus that caused the firing eventually would disappear. For example, a real duck might swim away or get a job in the movies. However, in the computer world, once data is stored, it stays there until explicitly removed or the power is turned off.

The following example shows activations and firing of a rule. Notice that the (watch) commands are used to more carefully show every fact and activation. The arrow going to the right means an entering fact or activation while an arrow to the left would mean an exiting fact or activation.

CLIPS> (clear)

CLIPS> (defrule duck

(animal-is duck)

=>

(printout t "quack" crlf))

CLIPS> (watch facts)

CLIPS> (watch activations)

CLIPS> (assert (animal-is duck))

==> f-0 (animal-is duck)

==> Activation 0 duck: f-0 ; Activation salience is 0 by <Fact-0> ; default, then rule name:pattern entity index

CLIPS> (assert (animal-is duck)) ; Notice that duplicate fact

FALSE ; cannot be entered

CLIPS> (agenda)

0 duck: f-0

For a total of 1 activation.

CLIPS> (run)

quack

CLIPS> (agenda) ; Nothing on agenda after rule fires

CLIPS> (facts) ; Even though fact matches rule, refraction

f-0 (animal-is duck); will not allow this activation because

For a total of 1 fact.; the rule already fired on this fact

CLIPS> (run)

CLIPS>

You can make the rule fire again if you retract the fact and then assert it as a new fact.

Show Me the Rules

Sometimes you may want to see a rule while you're in CLIPS. There's a command called ppdefrule - the pretty print rule - that prints a rule. To see a rule, specify the rule name as argument to pprule. For example,

CLIPS> (ppdefrule duck)

(defrule MAIN::duck

(animal-is duck)

=>

(assert (sound-is quack)))

CLIPS>

CLIPS puts different parts of the rule on different lines for the sake of readability. The patterns before the arrow are still considered the LHS and the actions after the arrow are still considered the RHS of the rule. The term MAIN refers to the MAIN module that this rule is in by default. You can define modules to put rules in analogous to the statements that may be put in different packages, modules, procedures, or functions of other programming languages. The use of modules make it easier to write expert systems having many rules since these may be grouped together with their own agendas for each module. For more information, see the CLIPS Reference Manual.

What if you want to print a rule but can't remember the name of the rule? No problem. Just use the rules command in response to a CLIPS prompt and CLIPS will print out the names of all the rules. For example, enter

CLIPS> (rules)

duck

For a total of 1 defrule.

CLIPS>

Write to Me

Besides asserting facts in the RHS of rules, you also can print out information using the printout function. CLIPS also has a carriage return/linefeed keyword called crlf which is very useful in improving the appearance of output by formatting it on different lines. For a change, the crlf is not included in parentheses. As an example,

CLIPS> (defrule duck

(animal-is duck)

=>

(printout t "quack" crlf)) ; Be sure to type in the "t"

CLIPS> (run)

quack

CLIPS>

The output is the text within the double quotes. Be sure to type the letter "t" following the printout command. This tells CLIPS to send the output to the standard output device of your computer. Generally, the standard output device is your terminal (hence the letter "t" after printout.) However, this may be redefined so that the standard output device is some other device, such as a modem or disk.

Other Features

The declare salience command provides explicit control over which rules will be put on the agenda. You must be careful in using this feature too freely lest your program become too controlled. The set-incremental-reset command prohibits rules from seeing facts that are entered before the rules are entered. The command to get the current value of incremental reset is getincrementalreset. One way to make a rule fire again is to force the rule to be re-activated by the refresh rule command.

The load command loads in the rule that you had previously saved to disk in the file "duck.clp" or whatever name and directory that you had saved it under. You can load a file of rules made on a text editor into CLIPS using the load command.

A faster way to load files is to first save them in a machine readable binary format with the save binary command called bsave. The load binary command, bload, can then be used to read these binary rules into CLIPS memory much faster since the files do not have to be re-interpreted by CLIPS.

Two other useful commands allow you to save and load facts using a file. These are save-facts and load-facts. The (save-facts) will save all the facts in the fact-list to a file while (load-facts) will load in the facts from a file into the fact-list.

The batch command allows you to execute commands from a file as if they were typed in at the top-level.Another useful command provides an interface to your operating system. The system command allows the execution of operating system commands or executables within CLIPS. For more information on all these topics, see the CLIPS Reference Manual.

Chapter 3 Adding Details

It's not the big picture that is the problem--it's the details

In the first two chapters, you learned the fundamentals of CLIPS. Now you will see how to build on that foundation to create more powerful programs.

Stop And Go

Until now, you've only seen the simplest type of program consisting of just one rule. However, expert systems consisting of only one rule are not very useful. Practical expert systems may consist of hundreds or thousands of rules. Let's now take a look at an application requiring multiple rules.

Suppose you wanted to write an expert system to determine how a mobile robot should respond to a traffic light. It is best to write this type of problem using multiple rules. For example, the rules for the red and green light situations can be written as follows.

(defrule red-light

(light red)

=>

(printout t "Stop" crlf))

(defrule green-light

(light green)

=>

(printout t "Go" crlf))

After the rules have been entered into CLIPS, assert a fact (light red) and run. You'll see "Stop" printed. Now assert a (light green) fact and run. You should see "Go" printed.

Take a Walk

If you think about it, other possibilities beside the simple red, green, and yellow cases exist. Some traffic lights also have a green arrow for protected left turns. Some have a hand that lights up to indicate whether a person can walk or not. Some have signs that say walk or don't walk. So depending on whether our robot is walking or driving, it may have to pay attention to different signs.

The information about walking or driving must be asserted in addition to information about the status of the light. Rules can be made to cover these conditions, but they must have more than one pattern. For example, suppose we want a rule to fire if the robot is walking and if the walk-sign says walk. A rule could be written as follows:

(defrule take-a-walk

(status walking)

(walk-sign walk)

=>

(printout t "Go" crlf))

The above rule has two patterns. Both patterns must be satisfied by facts in the fact- list for the rule to fire. To see how this works, enter the rule and then assert the facts (status walking) and (walk-sign walk). When you (run), the program will print out "Go" since both patterns are satisfied and the rule is fired.

You can have any number of patterns or actions in a rule. The important point to realize is that the rule is placed on the agenda only if all the patterns are satisfied by facts. This type of restriction is called a logical AND conditional element (CE)in reference to the AND relation of Boolean logic. An AND relation is said to be true only if all its conditions are true.

Because the patterns are of the logical AND type, the rule will not fire if only one of the patterns is satisfied. All facts must be present before the LHS of a rule is satisfied and the rule is placed on the agenda.

A Question of Strategy

The word strategy was originally a military term for the planning and operations of warfare. Today, the term strategy is commonly used in business (because business is war) to refer to the high-level plans of an organization in achieving its goals, e.g., "Make a lot of money by selling more greasy hamburgers than anyone else in the world!"

In expert systems, one use of the term strategy is in conflict resolution of activations. Now you might say, "Well, I'll just design my expert system so that only one rule can possibly be activated at one time. Then there is no need for conflict resolution." The good news is that if you succeed, conflict resolution is indeed unnecessary. The bad news is that this success proves that your application can be well represented by a sequential program. So you should have coded it in Ada, C, or Pascal in the first place and not bothered writing it as an expert system.

CLIPS offers seven different modes of conflict resolution: depth, breadth, LEX, MEA, complexity, simplicity, and random. It's difficult to say that one is clearly better than another without considering the specific application. Even then, it may be difficult to judge which is "best." For more information on the details of these strategies, see the CLIPS Reference Manual.

The depth strategy is the standard default strategy of CLIPS. The default setting is automatically set when CLIPS is first started. Afterwards, you can change the default setting. In the depth strategy, new activations are placed on the agenda after activations with higher salience, but before activations with equal or lower salience. All this simply means is that the agenda is ordered from highest to lowest salience.

In this book, all discussions and examples will assume depth strategy.

Now that all these different optional settings are available, be sure that before you run an expert system developed by someone else, that your settings are the same as theirs. Otherwise, you may find the operation is inefficient or even incorrect. In fact, it's a good idea to explicitly encode all the settings in any system that you develop so that it will be configured properly.

Gimme Deffacts

As you work with CLIPS, you may become tired of typing in the same assertions from the top-level. If you are going to use the same assertions every time a program is run, you can first load assertions from a disk using a batch file. An alternative way to enter facts is by using the define facts keyword, deffacts. For example,

CLIPS> (clear)

CLIPS> (deffacts walk "Some facts about walking"

(status walking) ; fact to be asserted

(walk-sign walk)) ; fact to be asserted

CLIPS> (reset) ; causes facts from defacts to be asserted

CLIPS> (facts)

f-0 (initial-fact)

f-1 (status walking)

f-2 (walk-sign walk)

For a total of 3 facts.

CLIPS>

The required name of this deffacts statement, walk, follows the deffacts keyword. Following the name is an optional comment in double quotes. Like the optional comment of a rule, the (deffacts) comment will be retained with the (deffacts) after it's been loaded by CLIPS. After the name or comment are the facts that will be asserted in the fact-list. The facts in a deffacts statement are asserted using the CLIPS (reset) command.

The (initial-fact) is put in automatically by a (reset). The fact-identifier of the initial-fact is always f-0. Even without any deffacts statements, a (reset) always will assert an (initial-fact).

The utility of (initial-fact) lies in starting the execution of a program. A CLIPS program will not start running unless there are rules whose LHS's are satisfied by facts. Rather than having to type in some fact to start things off, the (reset) command asserts it for you as well as asserting the facts in deffacts statements.

The (reset) has a further advantage compared to a (clear) command in that (reset) doesn't get rid of all the rules. The (reset) leaves your rules intact. Like (clear), it removes all activated rules from the agenda and also removes all old facts from the fact-list. Giving a (reset) command is a recommended way to start off program execution, especially if the program has been run before and the fact-list is cluttered with old facts.

In summary, the (reset) does three things for facts.

(1) It removes existing facts from the fact-list, which may remove activated rules from the agenda.

(2) It asserts (initial-fact).

(3) It asserts facts from existing (deffacts) statements.

Actually, the (reset) also does corresponding operations on objects. It deletes instances, creates initial-object, and asserts instances from definstances.

Selective Elimination

The undeffacts command excises a (deffacts) from asserting facts by eliminating the deffacts from memory. For example,

CLIPS> (undeffacts walk)

CLIPS> (reset)

CLIPS> (facts)

f-0 (initial-fact)

For a total of 1 fact.

CLIPS>

This example demonstrates how the (deffacts) walk has been excised. To restore a deffacts statement after an (undeffacts) command, you must enter the deffacts statement again. You can even get rid of initial-fact with (undeffacts). In addition to facts, CLIPS also allows you to eliminate rules selectively by using the undefrule.

Watch It!

You can watch rules firing and watch activations on the agend. The watch statistics prints information about the number of rules fired, run time, rules per second, mean number of facts, maximum number of facts, mean number of activations, and maximum number of activations. The statistics information may be useful in tuning up an expert system to optimize its speed. Another command, called watch compilations, shows information when rules are being loaded. The watch all command will watch everything.

Printing of watch information to the screen or to disk with the dribble command will slow down your program somewhat because CLIPS uses more time to print or to save to disk. The dribble-on command will store everything entered in the Dialog Window to a disk file until the dribble-off command is entered. This is convenient in providing a permanent record of everything that happens. These commands are as follows.

(dribble-on <filename>)

(dribble-off <filename>)

Another useful debugging command is (run) which takes an optional argument of the number of rule firings. For example, a (run 21) command would tell CLIPS to run the program and then stop after 21 rule firings. A (run 1) command allows you to step through a program firing one rule at a time. The (step) command is equivalent to (run 1).

Just like many other programming languages, CLIPS also gives you the capability of setting breakpoints. A breakpoint is simply an indicator to CLIPS to stop execution just prior to executing a specified rule. A breakpoint is set by the setbreak command. The remove-break command will remove a breakpoint that has been set. The show-breaks will list all the rules which have breakpoints set. The syntax of these rules for the argument <rulename> is shown following.

(set-break <rulename>)

(remove-break <rulename>)

(show-breaks)

A Good Match

You may encounter a situation in which you are certain a rule should be activated but isn't. While it is possible that this is due to a bug in CLIPS, it's not very likely because of the great skill of the people who programmed CLIPS (NOTE: PAID COMMERCIAL ANNOUNCEMENT FOR THE DEVELOPERS)

In most cases, the problem occurs because of the way that you wrote the rule. As an aid to debugging, CLIPS has a command called matches that can tell you which patterns in a rule match facts. Patterns which do not match prevent the rule from becoming activated. One common reason that a pattern won't match a fact results from misspelling an element in the pattern or in the assertion of the fact.

The argument of (matches) is the name of the rule to be checked for matches. To see how (matches) works, first (clear), then enter the following rule.

(defrule take-a-vacation

(work done) ; Conditional element 1

(money plenty) ; Conditional element 2

(reservations made) ; Conditional element 3

=>

(printout t "Let's go!!!" crlf))

The following shows how (matches) is used. Enter the commands as shown. Notice that (watch facts) is turned on. This is a good idea when you are asserting facts manually since it gives you an opportunity to check the spelling of facts.

CLIPS> (assert (work done))

==> f-0 (work done)

<Fact-0>

CLIPS> (matches take-a-vacation)

Matches for Pattern 1

f-0

Matches for Pattern 2

None

Matches for Pattern 3

None

Partial matches for CEs 1 - 2 ; CE is conditional element

None

Partial matches for CEs 1 - 3

None

Activations

None

CLIPS>

The fact with fact-identifier f-1 matches the first pattern or conditional element in the rule and is reported by (matches). Given that a rule has N patterns, the term partial matches refers to any set of matches of the first N-1 patterns with facts. That is, the partial matches begin with the first pattern in a rule and end with any pattern up to but not including the last (Nth) pattern. As soon as one partial match cannot be made, CLIPS does not check any further. For example, a rule with four patterns would have partial matches of the first and second patterns and also of the first, second, and third patterns. If all N patterns match, the rule will be activated.

Other Features

Some additional commands are useful with deffacts. For example, the command listdeffacts will list the names of currently loaded deffacts in CLIPS. Another useful command is ppdeffacts which prints the facts stored in a deffacts.

Other functions allow you to manipulate strings easily.

Function Meaning

assert-string Performs a string assertion by taking a string as argument and asserted as a nonstring fact.

str-cat Constructs a single-quoted string from individual items by string concatenation

str-index Returns a string index of first occurrence of a substring

sub-string Returns a substring from a string.

str-compare Performs a string compare

str-length Returns the string length which is the length of a string:

sym-cat Returns a concatenated symbol.

If you want to printout a multifield variable without parentheses, the simplest way is by using the string implode function, implode$.

Chapter 4 Variable Interests

Nothing changes more than change

The type of rules that you've seen so far illustrates simple matching of patterns to facts. In this chapter, you'll learn very powerful ways to match and manipulate facts.

Let's Get Variable

Just as with other programming languages, CLIPS has variables to store values. Unlike a fact, which is static or unchanging, the contents of a variable are dynamic as the values assigned to it change. In contrast, once a fact is asserted, it's fields can only be modified by retracting and asserting a new fact with the changed fields, Even the modify action (described later in the chapter on deftemplate) acts by retracting and asserting a modified fact, as you can see by checking the fact-index.

The name of a variable, or variable identifier, is always written by a question mark followed by a symbol that is the name of the variable. The general format is

?<variable-name>

Global variables, to be described in more detail later, have a slightly different syntax.

Just as in other programming languages, variable names should be meaningful for good style. Some examples of valid variable names follow.

?x ?noun ?color

?sensor ?valve ?ducks-eaten

Before a variable can be used, it should be assigned a value. As an example of a case where a value is not assigned, try to enter the following and CLIPS will respond with the error message shown.

CLIPS> (clear)

CLIPS> (defrule test

(initial-fact) ; asserted by a (reset) command

=>

(printout t ?x crlf))

Undefined variable x referenced in RHS of defrule.

ERROR:

(defrule MAIN::test

(initial-fact)

=>

(printout t ?x crlf))

CLIPS>

CLIPS gives an error message when it cannot find a value bound to ?x. The term bound means the assignment of a value to a variable. Only global variables are bound in all rules. All other variables are only bound within a rule. Before and after a rule fires, nonglobal variables are not bound and so CLIPS will give an error message if you try to query a nonbound variable.

Be Assertive

One common use of variables is to match a value on the LHS and then assert this bound variable on the RHS. For example, enter

(defrule make-quack

(duck-sound ?sound)

=>

(assert (sound-is ?sound)))

Now assert (duck-sound quack), then (run) the program. Check the facts and you'll see that the rule has produced (sound-is quack) because the variable ?sound was bound to quack.

Of course, you also can use a variable more than once. For example, enter the following. Be sure to do a (reset) and assert (duck-sound quack) again.

(defrule make-quack

(duck-sound ?sound)

=>

(assert (sound-is ?sound ?sound)))

When the rule fires, it will produce (sound-is quack quack) since the variable ?sound is used twice.

What the Duck Said

Variables also are used commonly in printing output, as in

(defrule make-quack

(duck-sound ?sound)

=>

(printout t "The duck said " ?sound crlf))

Do a (reset), enter this rule, and assert the fact and then (run) to find out what the duck said. How would you modify the rule to put double quotes around quack in the output?

More than one variable may be used in a pattern, as the following example shows.

CLIPS> (clear)

CLIPS> (defrule whodunit

(duckshoot ?hunter ?who)

=>

(printout t ?hunter " shot " ?who crlf))

CLIPS> (reset)

CLIPS> (assert (duckshoot Brian duck))

<Fact-1>

CLIPS> (run)

Brian shot duck ; Duck dinner tonight!

CLIPS> (assert (duckshoot duck Brian))

<Fact-2>

CLIPS> (run)

duck shot Brian ; Brian dinner tonight!

CLIPS> (assert (duckshoot duck)) ; Missing third field

<Fact-3>

CLIPS> (run)

CLIPS> ; Rule doesn't fire, no output

Notice what a big difference the order of fields makes in determining who shot who. You can also see that the rule did not fire when the single-field fact (duck) was asserted. The rule was not activated because no field of the fact matched the second pattern constraint, ?who.

The Happy Bachelor

Retraction is very useful in expert systems and usually done on the RHS rather than at the top-level. Before a fact can be retracted, it must be specified to CLIPS. To retract a fact from a rule, the fact-address first must be bound to a variable on the LHS.

There is a big difference between binding a variable to the contents of a fact and binding a variable to the fact-address. In the examples that you've seen such as (duck- sound ?sound), a variable was bound to the value of a field. That is, ?sound was bound to quack. However, if you want to remove the fact whose contents are (duck- sound quack), you must first tell CLIPS the address of the fact to be retracted.

The fact-address is specified using the left arrow, "<-". To create this, just type a "<" symbol followed by a "-". As an example of fact retraction from a rule,

CLIPS> (clear)

CLIPS> (assert (bachelor Dopey))

<Fact-0>

CLIPS> (facts)

f-0 (bachelor Dopey)

For a total of 1 fact.

CLIPS> (defrule get-married

?duck <- (bachelor Dopey)

=>

(printout t "Dopey is now happily married" ?duck crlf)

(retract ?duck))

CLIPS> (run)

Dopey is now happily married<Fact-0>

CLIPS> (facts)

CLIPS>

Notice that the (printout) prints the fact- index of ?duck, <Fact-0>, since the left arrow bound the address of the fact to ?duck. Also, there is no fact (bachelor Dopey) because it has been retracted.

Variables can be used to pick up a fact value at the same time as an address, as shown in the following example. For convenience, a (deffacts) has also been defined.

CLIPS> (clear)

CLIPS> (defrule marriage

?duck <- (bachelor ?name)

=>

(printout t ?name " is now happily married" crlf)

(retract ?duck))

CLIPS> (deffacts good-prospects

(bachelor Dopey)

(bachelor Dorky)

(bachelor Dicky))

CLIPS> (reset)

CLIPS> (run)

Dicky is now happily married

Dorky is now happily married

Dopey is now happily married

CLIPS>

Notice how the rule fired on all facts that matched the pattern (bachelor ?name). CLIPS also has a function called fact-index which can be used to return the fact index of a fact address.

It's Not Important

Instead of binding a field value to a variable, the presence of a nonempty field can be detected alone using a wildcard. For example, suppose you're running a dating service for ducks, and a duckette asserts that she only dates ducks whose first name is Richard. Actually, two criteria are in this specification since there is an implication that the duck must have more than one name. So a plain (bachelor Richard) isn't adequate because there is only one name in the fact.

This type of situation, in which only part of the fact is specified, is very common and very important. To solve this problem, a wildcard can be used to fire the Richards.

The simplest form of wildcard is called a single-field wildcard and is shown by a question mark, "?". The "?" is also called a single-field constraint. A single- field wildcard stands for exactly one field, as shown following.

CLIPS> (clear)

CLIPS> (defrule dating-ducks

(bachelor Dopey ?)

=>

(printout t "Date Dopey" crlf))

CLIPS>

(deffacts duck

(bachelor Dicky)

(bachelor Dopey)

(bachelor Dopey Mallard)

(bachelor Dinky Dopey)

(bachelor Dopey Dinky Mallard))

CLIPS> (reset)

CLIPS> (run)

Date Dopey

CLIPS>

The pattern includes a wildcard to indicate that Dopey's last name is not important. So long as the first name is Dopey, the rule will be satisfied and fire. Because the pattern has three fields of which one is a single-field wildcard, only facts of exactly three fields can satisfy it. In other words, only Dopeys with exactly two names can satisfy this duckette.

Suppose you want to specify Dopeys with exactly three names? All that you'd have to do is write a pattern like

(bachelor Dopey ? ?)

or, if only persons with three names whose middle name was Dopey,

(bachelor ? Dopey ?)

or, if only the last name was Dopey, as in the following:

(bachelor ? ? Dopey)

Another interesting possibility occurs if Dopey must be the first name, but only those Dopeys with two or three names are acceptable. One way of solving this problem is to write two rules. For example

(defrule eligible

(bachelor Dopey ?)

=>

(printout t "Date Dopey" crlf))

(defrule eligible-three-names

(bachelor Dopey ? ?)

=>

(printout t "Date Dopey" crlf))

Enter and run this and you'll see that Dopeys with both two and three names are printed. Of course, if you don't want anonymous dates, you need to bind the Dopey names with a variable and print them out.

Going Wild

Rather than writing separate rules to handle each field, it's much easier to use the multifield wildcard. This is a dollar sign followed by a question mark, "$?", and represents zero or more fields. Notice how this contrasts with the single-field wildcard which must match exactly one field.

The two rules for dates can now be written in a single rule as follows.

CLIPS> (clear)

CLIPS> (defrule dating-ducks

(bachelor Dopey $?)

=>

(printout t "Date Dopey" crlf))

CLIPS> (deffacts duck

(bachelor Dicky)

(bachelor Dopey)

(bachelor Dopey Mallard)

(bachelor Dinky Dopey)

(bachelor Dopey Dinky Mallard))

CLIPS> (reset)

CLIPS> (run)

Date Dopey

Date Dopey

Date Dopey

CLIPS>

Wildcards have another important use because they can be attached to a symbolic field to create a variable such as ?x, $?x, ?name, or $?name. The variable can be a singlefield variable or a multifield variable depending on whether a "?" or "$?" is used on the LHS. Note that on the RHS only a ?x is used, where the "x" can be any variable name. You can think of the "$" as a function whose argument is a single-field wildcard or a single-field variable and returns a multifield wildcard or a multifield variable, respectively.

As an example of a multifield variable, the following version of the rule also prints out the name field(s) of the matching fact because a variable is equated to the name field(s) that match:

CLIPS> (defrule dating-ducks

(bachelor Dopey $?name)

=>

(printout t "Date Dopey " ?name crlf))

CLIPS> (reset)

CLIPS> (run)

Date Dopey (Dinky Mallard)

Date Dopey (Mallard)

Date Dopey ()

CLIPS>

As you can see, on the LHS, the multifield pattern is $?name but is ?name when used as a variable on the RHS. When you enter and run, you'll see the names of all eligible Dopeys. The multifield wildcard takes care of any number of fields. Also, notice that multifield values are returned enclosed in parentheses.

Suppose you wanted a match of all ducks who had a Dopey somewhere in their name, not necessarily as their first name. The following version of the rule would match all facts with a Dopey in them and then print out the names:

CLIPS> (defrule dating-ducks

(bachelor $?first Dopey $?last)

=>

(printout t "Date " ?first " Dopey " ?last crlf))

CLIPS> (reset)

CLIPS> (run)

Date () Dopey (Dinky Mallard)

Date (Dinky) Dopey ()

Date () Dopey (Mallard)

Date () Dopey ()

CLIPS>

The pattern matches any names that have a Dopey anywhere in them.

Single- and multifield wildcards can be combined. For example, the pattern

(bachelor ? $? Dopey ?)

means that the first and last names can be anything and that the name just prior to the last must be Dopey. This pattern also requires that the matching fact will have at least four fields, since the "$?" matches zero or more fields and all the others must match exactly four.

Although multifield variables can be essential for pattern matching in many cases, their overuse can cause much inefficiency because of increased memory requirements and slower execution.

_ As a general rule of style, you should use $? only when you don't know the length of fields. Do not use $? simply as a typing convenience.

The Ideal Bachelor

Variables used in patterns have an important and useful property, which can be stated as follows.

_ The first time a variable is bound it retains that value only within the rule, both on the LHS and also on the RHS, unless changed on the RHS.

For example, in the rule below

(defrule bound

(number-1 ?num)

(number-2 ?num)

=>)

If there are some facts

f-0 (number-1 0)

f-1 (number-2 0)

f-2 (number-1 1)

f-3 (number-2 1)

then the rule can only be activated by the pair f-0, f-1, and the other pair f-2, f-3. That is, fact f-0 cannot match with f-3 because when ?num is bound to 0 in the first pattern, the value of ?num in the second pattern also must be 0. Likewise, when ?num is bound to 1 in the first pattern, the value of ?num in the second pattern must be 1. Notice that the rule will be activated twice by these four facts: one activation for the pair f-0, f-1, and the other activation for the pair f-2, f-3.

As a more practical example, enter the following rule. Notice that the same variable, ?name, is used in both patterns. Before doing a (reset) and (run), also enter a (watch all) command so that you can see what happens during execution.

CLIPS> (clear)

CLIPS> (defrule ideal-duck-bachelor

(bill big ?name)

(feet wide ?name)

=>

(printout t "The ideal duck is " ?name crlf))

CLIPS> (deffacts duck-assets

(bill big Dopey)

(bill big Dorky)

(bill little Dicky)

(feet wide Dopey)

(feet narrow Dorky)

(feet narrow Dicky))

CLIPS> (reset)

CLIPS> (run)

The ideal duck is Dopey

CLIPS>

When the program is run, the first pattern matches Dopey and Dorky since they both have big bills. The variable ?name is bound to each name. When CLIPS tries to match the second pattern of the rule, only the variable ?name which is bound to Dopey also satisfies the second pattern of (feet wide).

The Lucky Duck

Many situations occur in life where it's wise to do things in a systematic manner. That way, if your expectations don't work out you can try again systematically (such as the common algorithm for finding the Perfect Spouse by getting married over and over again).

One way of being organized is to keep a list (Note: if you really want to impress people, show them a list of your lists.) In our case, we'll keep a list of duck bachelors, with the most likely prospect for matrimony at the front. Once an ideal duck bachelor has been identified, we'll shoot him up to the front of the list as the lucky duck.

The following program shows how this can be done by adding a couple of rules to the ideal ?duck-bachelor rule.

(defrule ideal-duck-bachelor

(bill big ?name)

(feet wide ?name)

=>

(printout t "The ideal duck is " ?name crlf)

(assert (move-to-front ?name)))

(defrule move-to-front

?move-to-front <- (move-to-front ?who)

?old-list <- (list $?front ?who $?rear)

=>

(retract ?move-to-front ?old-list)

(assert (list ?who ?front ?rear))

(assert (change-list yes)))

(defrule print-list

?change-list <- (change-list yes)

(list $?list)

=>

(retract ?change-list)

(printout t "List is : " ?list crlf))

(deffacts duck-bachelor-list

(list Dorky Dinky Dicky))

(deffacts duck-assets

(bill big Dicky)

(bill big Dorky)

(bill little Dinky)

(feet wide Dicky)

(feet narrow Dorky)

(feet narrow Dinky))

The original list is given in the duck ?duck-bachelor-list deffacts. When the program is run, it will provide a new list of likely candidates.

CLIPS> (reset)

CLIPS> (run)

The ideal duck is Dicky

List is : (Dicky Dorky Dinky)

CLIPS>

Notice the assertion (change-list yes) in the move-to-front rule. Without this assertion, the print-list rule would always fire on the original list. This assertion is an example of a control fact made to control the firing of another rule. Control facts are very important in controlling the activation of certain rules, and you should study this example carefully to understand why it's used. Another method of control is modules, as discussed in the CLIPS Reference Manual.

The move-to-front rule removes the old list and asserts the new list. If the old list was not retracted, two activations would be on the agenda for the print-list rule but only one would fire. Only one will fire because the print-list rule removes the control fact required for the other activation of the same rule. You would not know in advance which one would fire, so the old list might be printed instead of the new list.

Chapter 5 Doing It Up In Style

Style today, gone tomorrow

In this chapter, you will learn about a keyword called deftemplate, which stands for define template. This feature can aid you in writing rules whose patterns have a well-defined structure.

Mr. Wonderful

Deftemplate is analogous to a record structure in Pascal. That is, the deftemplate defines a group of related fields in a pattern similar to the way in which a Pascal record is a group of related data. A deftemplate is a list of named fields called slots. Deftemplate allows access by name rather than by specifying the order of fields. Deftemplate contributes to good style in expert systems programs and is a valuable tool of software engineering.

A slot is a named single-slot or multislot. A single-slot or simply slot contains exactly one field while a multislot contains zero or more fields. Any number of single or multislot slots may be used in a deftemplate. To write a slot, give the field name (attribute) followed by the field value. Note that a multislot slot with one value is strictly not the same as a single-slot slot. As an analogy, think of a cupboard (the multislot) that may contain dishes. A cupboard with one dish is not the same as a dish (single-slot.) However, the value of a single-slot slot (or variable) may match a multislot slot (or multislot variable) that has one field.

As an example of a deftemplate relation, consider the attributes of a duck who might be considered a good matrimonial prospect.

Attributes Value

name "Dopey Wonderful"
assets rich
age 99

A deftemplate may be defined for the relation prospect as follows, where white space and comments are used for readability and explanation.

(deftemplate prospect ;name of deftemplate relation

"vital information" ;optional comment in quotes

(slot name ;name of field

(type STRING) ;type of field

(default ?DERIVE)) ;default value of field name

(slot assets ;name of field

(type SYMBOL) ;type of field

(default rich)) ;default value of field assets

(slot age ;name of field

(type NUMBER) ;type. NUMBER can be INTEGER or FLOAT

(default 80))) ;default value of field age

In this example, the components of deftemplate are structured as:

_ A deftemplate relation name

_ Attributes called fields

_ The field type, which can be any one of the allowed types:
SYMBOL, STRING, NUMBER, and others.

_ The default for the field value

This particular deftemplate has three single-slot slots called name, assets, and age.

The deftemplate default values are inserted by CLIPS when a (reset) is done if no explicit values are defined. For example, enter the deftemplate for prospect, and assert it as shown.

CLIPS> (assert (prospect))

<Fact-0>

CLIPS> (facts)

f-0 (prospect (name "") (assets rich) (age 80))

For a total of 1 fact.

CLIPS>

As you can see, CLIPS has inserted the default value of the null string, "", for the name field since that is the default for a STRING. Likewise, the assets and age defaults were also inserted by CLIPS. Different types have different default symbols such as the null string, "", for STRING; the integer 0 for INTEGER; the float 0.0 for FLOAT and so on. The ?DERIVE keyword selects the appropriate type of constraint for that slot, e.g., the null string , "", for a slot of type STRING.

You can explicitly set the field values, as the following example shows.

CLIPS> (assert (prospect (age 99) (name "Dopey"))))

CLIPS> (facts)

f-0 (prospect (name "") (assets rich) (age 80))

f-1 (prospect (name "Dopey") (assets rich) (age 99))

For a total of 2 facts.

CLIPS>

Note that the order that the fields are typed in does not matter since these are named fields.

In the deftemplate, it's important to realize that NUMBER is not a primitive field type like symbol, string, integer, and float. The NUMBER is really a compound type that can be integer or float. It is used for cases in which the user doesn't care what type of numbers are stored. An alternative to NUMBER would be specifying the types as follows.

(slot age

(type INTEGER FLOAT)

(default 80)))

Bye-Bye

In general, a deftemplate with N slots has the following general structure:

(deftemplate <name>

(slot-1)

(slot-2)

...

(slot-N))

In a deftemplate, the attribute values may be specified more precisely than a simple value such as 80 or rich. For example, in this deftemplate, a type of value is specified.

The field values can be specified by either explicitly listing them or giving a range of values. The allowed-values can be any primitive type such as SYMBOL, STRING, INTEGER, FLOAT and so on. For example,

Deftemplate Enumerated Values Example

allowed-symbols rich filthy-rich loaded

allowed-strings "Dopey" "Dorky" "Dicky"

allowed-numbers 1 2 3 4.5 -2.001 1.3e-4

allowed-integers -100 53

allowed-floats -2.3 1.0 300.00056

allowed-values "Dopey" rich 99 1.e9

It doesn't make sense to specify both a numeric range and values allowed for the same deftemplate field. For example, if you specify (allowed-integers 1 4 8), this contradicts a range specification of 1 to 10 by (range 1 10). If the numbers happen to be sequential, such as 1, 2, 3, then you could specify a range which would exactly match: (range 1 3). However, the range would be redundant to the allowed-integers specification. Thus, range and allowed values are mutually exclusive. That is, if you specify a range, you can't specify the allowed values and vice versa. In general, the range attribute cannot be used in conjunction with allowed-values, allowed-numbers, allowed-integers, or allowed-floats.

Without the optional information, the deftemplate and a rule which uses it follows.

(clear)

(deftemplate prospect ;name of deftemplate

(slot name ;name of field

(default ?DERIVE)) ;default value of field name

(slot assets ;name of field

(default rich)) ;default value of field assets

(slot age ;name of field

(default 80))) ;default value of field age

(defrule matrimonial_candidate

(prospect (name ?name) (assets ?net_worth) (age ?months))

=>

(printout t "Prospect: " ?name crlf

?net_worth crlf

?months " months old" crlf crlf))

CLIPS> (assert (prospect (name "Dopey Wonderful") (age 99)))

<Fact-0>

CLIPS> (run)

Prospect: Dopey Wonderful

rich

99 months old

CLIPS>

Notice that the default value of rich was used for Dopey since the assets field was not specified in the assert command.

If the assets field is given a specific value such as poor, the specified value for assets of poor overrides the default value of rich as shown in the following example about Dopey's penurious nephew.

CLIPS> (reset)

CLIPS> (assert (prospect (name "Dopey Notwonderful")

(assets poor) (age 95)))

CLIPS> (run)

Prospect: "Dopey Notwonderful"

poor

95 months old

A deftemplate pattern may be used just like any ordinary pattern. For example, the following rule will eliminate undesirable prospects.

CLIPS> (undefrule matrimonial_candidate)

CLIPS> (defrule bye-bye

?bad-prospect <- (prospect (assets poor) (name ?name))

=>

(retract ?bad-prospect)

(printout t "bye-bye " ?name crlf))

CLIPS> (reset)

CLIPS> (assert (prospect (name "Dopey Wonderful") (assets rich)))

<Fact-1>

CLIPS> (assert (prospect (name "Dopey Notwonderful") (assets poor)))

<Fact-2>

CLIPS> (run)

bye-bye Dopey Notwonderful

CLIPS>

Ain't No Strings on Me

Notice that only single fields were used for the patterns in the examples so far. That is, the field values for name, assets, and age, were all single values. In some types of rules, you may want multiple fields. Deftemplate allows the use of multiple values in a multislot.

As an example of multislot, suppose that you wanted to treat the name of the relation prospect as multiple fields. This would provide more flexibility in processing prospects since any part of the name could be pattern matched. Shown following is the deftemplate definition using multislot and the revised rule to pattern match on multiple fields. Notice that a multislot pattern, $?name, is now used to match all the fields that make up the name. For convenience, a (deffacts) is also given.

CLIPS> (clear)

CLIPS> (deftemplate prospect

(multislot name

(type SYMBOL)

(default ?DERIVE))

(slot assets

(type SYMBOL)

(allowed-symbols poor rich wealthy loaded)

(default rich))

(slot age

(type INTEGER)

(range 80 ?VARIABLE) ; The older the better!!!

(default 80)))

CLIPS> (defrule happy_relationship

(prospect (name $?name) (assets ?net_worth) (age ?months))

=>

(printout t "Prospect: " ?name crlf ; Note: not ?name

?net_worth crlf

?months " months old" crlf crlf))

CLIPS> (deffacts duck-bachelor

(prospect (name Dopey Wonderful) (assets rich) (age 99)))

CLIPS> (reset)

CLIPS> (run)

Prospect: (Dopey Wonderful)

rich

99 months old

CLIPS>

In the output, the parentheses around Dopey's name are put in by CLIPS to indicate that this is a multislot value. If you compare the output from this multislot version to the single-slot version, you'll see that the double quotes around "Dopey Wonderful" are gone. The name slot is not a string in the multislot version, so CLIPS treats the name as two independent fields, Dopey and Wonderful.

What's in a Name

Deftemplate greatly simplifies accessing a specific field in a pattern because the desired field can be identified by its slot name. The modify action can be used to retract and assert a new fact in one action by specifying one or more template slots to be modified.

As an example, consider the following rules which show what happens when duck- bachelor Dopey Wonderful loses all his fish buying Donald Duck posters and banana fishsplits for his new duckette, Dixie.

CLIPS> (undefrule *)

CLIPS>

(defrule make-bad-buys

?prospect <- (prospect (name $?name)

(assets rich)

(age ?months))

=>

(printout t "Prospect: " ?name crlf ; Note: not ?name

"rich" crlf

?months " months old" crlf crlf)

(modify ?prospect (assets poor)))

CLIPS>

(defrule poor-prospect

?prospect <- (prospect (name $?name)

(assets poor)

(age ?months))

=>

(printout t "Ex-prospect: " ?name crlf ; Note: not ?name

poor crlf

?months " months old" crlf crlf))

CLIPS> (deffacts duck-bachelor

(prospect (name Dopey Wonderful) (assets rich) (age 99)))

CLIPS> (reset)

CLIPS> (run)

Prospect: (Dopey Wonderful)

rich

99 months old

Ex-prospect: (Dopey Wonderful)

poor

99 months old

CLIPS>

If you do a (facts) command as follows, you'll see that the f-1 fact corresponding to (prospect (assets rich) (age 99) (name Dopey Wonderful)) is gone since the (modify) has retracted it and asserted f-2.

CLIPS> (facts)

f-0 (initial-fact)

f-2 (prospect (name Dopey Wonderful) (assets poor) (age 99))

For a total of 2 facts.

CLIPS>

The make-bad- buys rule is activated by a rich prospect as specified by the assets slot. This rule changes the assets to poor using the modify action. Notice that the slot assets can be accessed by name. Without a deftemplate, it would be necessary to enumerate all the fields by single variables or by using a wildcard, which is less efficient. The purpose of the poor- prospect rule is simply to print out the poor prospects, thus demonstrating that the make-bad-investments rule did indeed modify the assets.

Chapter 6 Being Functional

Functionality is the inverse of style

In this chapter, you will learn more powerful functions for matching patterns and some that are very useful with multifield variables. You also will learn how numeric calculations are done.

Not My Constraint

Let's reconsider the problem of designing an expert system to help a robot cross a street. One rule that you would have follows.

(defrule green-light

(light green)

=>

(printout t "Walk" crlf))

Another rule would cover the case of a red light.

(defrule red-light

(light red)

=>

(printout t "Don't walk" crlf))

A third rule would cover the case in which a walk-sign said not to walk. This would take precedence over a green light.

(defrule walk-sign

(walk-sign-says dont-walk)

=>

(printout t "Don't walk" crlf))

The previous rules are simplified and don't cover all cases such as the breakdown of the traffic-light. For example, what does the robot do if the light is red or yellow and the walk-sign says walk?

A way of handling this case is to use a field constraint to restrict the values that a pattern may have on the LHS. The field constraint acts like constraints on patterns.

One type of field constraint is called a connective constraint. There are three types of connective constraints. The first is called a ~ constraint. Its symbol is the tilde "~". The ~ constraint acts on the one value that immediately follows it and will not allow that value.

As a simple example of the ~ constraint, suppose you wanted to write a rule that would print out "Don't walk" if the light was not green. One approach would be to write rules for every possible light condition, including all possible malfunctions: yellow, red, blinking yellow, blinking red, blinking green, winking yellow, blinking yellow and winking red, and so forth. However, a much easier approach is to use the ~ constraint as shown in the following rule:

(defrule walk

(light ~green)

=>

(printout t "Don't walk" crlf))

By using the ~ constraint, this one rule does the work of many other rules that required specifying each light condition.

Be Cautious

The second connective constraint is the bar constraint, "|". The "|" connective constraint is used to allow any of a group of values to match.

For example, suppose you wanted a rule that printed out "Be cautious" if the light was yellow or blinking yellow. The following example shows how it's done using the "|" constraint.

CLIPS> (clear)

CLIPS> (defrule cautious

(light yellow|blinking-yellow)

=>

(printout t "Be cautious" crlf))

CLIPS>

(assert (light yellow))

<Fact-0>

CLIPS> (assert (light blinking-yellow))

<Fact-1>

CLIPS> (agenda)

0 cautious: f-1

0 cautious: f-0

For a total of 2 activations.

CLIPS>

And Away We Go

The third type of connective constraint is the & connective constraint. The symbol of the & connective constraint is the ampersand, "&". The & constraint forces connected constraints to match in union, as you'll see in the following examples. The & constraint normally is used only with the other constraints, otherwise it's not of much practical use. As an e xample, suppose you want to have a rule that will be triggered by a yellow or blinking-yellow fact. That's easy enough--just use the | connective constraint as you did in a previous example. But suppose that you also want to identify the light color?

The solution is to bind a variable to the color that is matched using the "&" and then print out the variable. This is where the "&" is useful, as shown below.

(defrule cautious

(light ?color&yellow|blinking-yellow)

=>

(printout t "Be cautious because light is " ?color crlf))

The variable ?color will be bound to whatever color is matched by the field yellow|blinking-yellow.

The "&" also is useful with the "~". For example, suppose you want a rule that triggers when the light is not yellow and not red.

(defrule not-yellow-red

(light ?color&~red&~yellow)

=>

(printout t "Go, since light is " ?color crlf))

It's Elementary

Besides dealing with symbolic facts, CLIPS also can perform numeric calculations. However, you should keep in mind that an expert system language like CLIPS is not primarily designed for number-crunching. Although the math functions of CLIPS are very powerful, they are really meant for modification of numbers that are being reasoned about by the application program. Other languages such as FORTRAN are better for number-crunching in which little or no symbolic reasoning is being done. You'll find the computational capability of CLIPS useful in many applications.

CLIPS provides basic arithmetic and math functions +, /, *, -, div, max, min, abs, float, and integer. For more details, see the CLIPS Reference Manual.

Numeric expressions are represented in CLIPS according to the style of LISP. In both LISP and CLIPS, a numeric expression that customarily would be written as 2 + 3 must be written in prefix form, (+ 2 3). In the prefix form of CLIPS, the function precedes the arguments, and parentheses must surround the numeric expression. The customary way of writing numeric expressions is called infix form because the math functions are fixed in between the arguments.

Functions can be used on the LHS and the RHS. For example, the following shows how the arithmetic operation of addition is used on the RHS of a rule to assert a fact containing the sum of two numbers ?x and ?y. Note that the comments are in infix notation for your information only since infix cannot be evaluated by CLIPS.

CLIPS> (clear)

CLIPS> (defrule addition

(numbers ?x ?y)

=>

(assert (answer-plus (+ ?x ?y)))) ; Add ?x + ?y

CLIPS> (assert (numbers 2 3))

<Fact-0>

CLIPS> (run)

CLIPS> (facts)

f-0 (numbers 2 3)

f-1 (answer-plus 5)

For a total of 2 facts.

CLIPS>

A function can be used on the LHS if an equal sign, =, is used to tell CLIPS to evaluate the following expression rather than use it literally for pattern matching. The following example shows how the hypotenuse is calculated on the LHS and used to pattern match against some stock items. The exponentiation, "**", function is used to square the x and y values. The first argument of exponentiation is the number which is to be raised to the power of the second argument.

CLIPS> (clear)

CLIPS> (deffacts database

(stock A 2.0)

(stock B 5.0)

(stock C 7.0))

CLIPS> (defrule addition

(numbers ?x ?y)

(stock ?ID =(sqrt (+ (** ?x 2) (** ?y 2)))) ; Hypotenuse

=>

(printout t "Stock ID=" ?ID crlf))

CLIPS> (reset)

CLIPS> (assert (numbers 3 4))

<Fact-4>

CLIPS> (run)

Stock ID=B : Stock ID matches hypo tenuse calculated

CLIPS>

Extensive Arguments

Arguments in a numeric expression can be extended beyond two for all functions except The same sequence of arithmetic calculations is performed for more than two arguments. The following example illustrates how three arguments are used. Evaluation proceeds from left to right. Before entering these, however, you may wish to do a (clear) to get rid of any old facts and rules.

(defrule addition

(numbers ?x ?y ?z)

=>

(assert (answer-plus (+ ?x ?y ?z)))) ; ?x + ?y + ?z

Enter the above program and assert (numbers 2 3 4). After you run, you'll see the following facts. Note that the fact-indices may be different if you've done a (reset) instead of a (clear) before loading this program.

CLIPS> (facts)

f-0 (numbers 2 3 4)

f-1 (answer-plus 9)

For a total of 2 facts.

CLIPS>

The infix equivalent of a multiple argument CLIPS expression can be expressed as

arg [function arg]

where the square brackets mean that there can be multiple terms.

Besides the basic math functions, CLIPS has Extended Math functions including trig, hyperbolic, and so on. For a complete list, see the CLIPS Reference Manual. These are called Extended Math functions because they are not considered basic math functions like "+", "-", etc.

Mixed Results

In dealing with expressions, CLIPS tries to keep the mode the same as the arguments. For example,

CLIPS> (+ 2 2) ;both integer arguments give integer

4 ;result

CLIPS> (+ 2.0 2.0) ;both floating-point arguments give

4.0 ;floating-point result

CLIPS> (+ 2 2.0) ; mixed arguments give float result

4.0

Notice that in the last case of mixed arguments, CLIPS converts the result to standard double-precision floating-point type.

You can explicitly convert one type to another by using the float and integer functions, as demonstrated in the following examples.

CLIPS> (float (+ 2 2)) ;convert integer to float

4.0

CLIPS> (integer (+ 2.0 2.0)) ; convert float to integer

4

Parentheses are used to explicitly specify the order of expression evaluation if desired. In the example of ?x + ?y * ?z, the customary infix way to evaluate it is to multiply ?y by ?z and then add the result to ?x. However, in CLIPS, you must write the precedence explicitly if you want this order of evaluation, as follows.

(defrule mixed-calc

(numbers ?x ?y ?z)

=>

(assert (answer (+ ?x (* ?y ?z))))) ; ?y * ?z + ?x

In this rule, the expression in the innermost parentheses is evaluated first; so ?y is multiplied by ?z. The result is added to ?x.

Bound Bachelors

The analog to assigning a value to a variable on the LHS by pattern matching is binding a value to a variable on the RHS using the bind function. It's convenient to bind variables on the RHS if the same values will be repeatedly used.

As a simple example in a math calculation, let's first bind the answer to a variable and then print the bound variable.

CLIPS> (clear)

CLIPS> (defrule addition

(numbers ?x ?y)

=>

(assert (answer (+ ?x ?y)))

(bind ?answer (+ ?x ?y))

(printout t "answer is " ?answer crlf))

CLIPS>

(assert (numbers 2 2))

<Fact-0>

CLIPS> (run)

answer is 4

CLIPS> (facts)

f-0 (numbers 2 2)

f-1 (answer 4)

For a total of 2 facts.

CLIPS>

The (bind) also can be used on the RHS to bind sin gle or multifield values to a variable. The (bind) is used to bind zero, one, or more values to a variable without the "$" operator. Recall that on the LHS, you can only create a multifield pattern by using the "$" operator on a field, such as "$?x". However, the "$" is unnecessary on the RHS because the arguments of (bind) explicitly tell CLIPS exactly how many values to bind. In fact, the "$" is a useless appendage on the RHS.

The following rule illustrates some variable bindings on the RHS. The multifield value function, create$, is used to create a multifield value. Its general syntax is as follows.

(create$ <arg1> <arg2>...<argN>)

where any number of arguments can be appended together to create a multifield value. This multifield value, or a single-field value, can then be bound to a variable as shown in the RHS actions of the following rule.

(CLIPS> (clear)

CLIPS> (defrule bind-values-demo

(initial-fact)

=>

(bind ?duck-bachelors (create$ Dopey Dorky Dinky))

(bind ?happy-bachelor-mv (create$ Dopey))

(bind ?none (create$))

(printout t

"duck-bachelors " ?duck-bachelors crlf

"duck-bachelors-no-() " (implode$ ?duck-bachelors) crlf

"happy-bachelor-mv " ?happy-bachelor-mv crlf

"none " ?none crlf))

CLIPS> (reset)

CLIPS> (run)

duck-bachelors (Dopey Dorky Dinky)

duck-bachelors-no-() Dopey Dorky Dinky

happy-bachelor-mv (Dopey)

none ()

CLIPS>

Doing Your Own Thing

Just like other languages, CLIPS allows you to define your own functions with deffunction. The deffunction is known globally, which saves you the effort of entering the same actions over and over again.

Deffunctions also help in readability. You can call a deffunction just like any other function. A deffunction may also be used as the argument of another function. A (printout) can be used anywhere in a deffunction even if it's not the last action because printing is a side-effect of calling the (printout) function.

The general syntax of a deffunction is shown following.

(deffunction <function-name> [optional comment]

(?arg1 ?arg2 ...?argM [$?argN]) ;argument list. Last one may

(<action1> ;be optional multifield arg.

<action2> ;action1 to

... ;action(K-1) do not

<action(K-1)> ;return a value

<actionK>) ;only last action returned

The ?arg are dummy arguments, which mean that the names of the arguments will not conflict with variable names in a rule if they are the same. The term dummy argument is sometimes called a parameter in other books.

Although each action may have returned values from function calls within the action, these are blocked by the deffunction from being returned to the user. The deffunction will only return the value of the last action, <actionK>. This action may be a function, a variable, or a constant.

The following is an example of how a deffunction is defined to calculate the hypotenuse, and then used in a rule. Even if the variable names in the rule are the same as the dummy arguments, there's no conflict. That's why they're dummy, because they don't mean anything.

CLIPS> (clear)

CLIPS> (deffunction hypotenuse ; name

(?a ?b) ; dummy arguments

(sqrt(+ (* ?a ?a) (* ?b ?b)))) ; action

CLIPS> (defrule calculate-hypotenuse

(dimensions ?base ?height)

=>

(printout t "Hypotenuse=" (hypotenuse ?base ?height) crlf))

CLIPS> (assert (dimensions 3 4))

<Fact-0>

CLIPS> (run)

Hypotenuse=5.0

CLIPS>

Deffunctions may be used with multifield values, as the following example shows.

CLIPS> (clear)

CLIPS> (deffunction count ($?arg)

(length $?arg))

CLIPS> (count 1 2 3 a duck "quacks")

6

CLIPS>

Other Features

Other useful functions follow. For more information, see the CLIPS Reference Manual.

Function Meaning

round Round toward closest integer. If exactly between two integers, rounds toward negative infinity.

integer Truncates the decimal part of a number.

format Formats output

list-deffunctions List all deffunctions

ppdeffunction Pretty print

undeffunction Deletes a deffunction if it is not currently executing and not referred to elsewhere. Specifying "*" for <name> deletes all.

length Number of fields, or the number of characters in a string or symbol

nth$ Specified field if exists, else nil

member$ Number of the field if literal or variable exists, else FALSE

subsetp Returns TRUE if a multifield value is a subsetp of another multifield value, else FALSE

delete$ Given a field number, deletes the value in the field

explode$ Each string element is returned as part of a new multifield value

subseq$ Returns a specified range of fields

replace$ Replaces a specified value

Chapter 7 How to Be in Control

When you're young, you're controlled by the world, when you're older, you should control the world

Up to this point, you've been learning the basic syntax of CLIPS. Now you'll see how to apply the syntax you've learned to more powerful and complex programs. You'll also learn some new syntax for input, and see how to compare values and generate loops.

Let's Start Reading

Besides matching a pattern, a rule can get information in another way. CLIPS can read the information that you type from the keyboard using the read function.

The following example shows how (read) is used to input data. Note that no extra (crlf) is needed after the (read) to put the cursor on a new line. The (read) automatically resets the cursor to a new line.

CLIPS> (clear)

CLIPS> (defrule read-input

(initial-fact)

=>

(printout t "Name a primary color" crlf)

(assert (color (read))))

CLIPS>

(defrule check-input

?color <- (color ?color-read&red|yellow|blue)

=>

(retract ?color)

(printout t "Correct" crlf))

CLIPS> (reset)

CLIPS> (run)

Name a primary color

red

Correct

CLIPS> (reset)

CLIPS> (run)

Name a primary color

green

CLIPS> ; No "correct"

The rule is designed to use keyboard input on the RHS, so it's convenient to trigger the rule with (initial-fact). Otherwise, you'd have to make up some dummy fact to trigger the rule.

The (read) function is not a general-purpose function that will read anything you type on the keyboard. One limitation is that (read) will read only one field. So if you try to read

primary color is red

only the first field, "primary", will be read. To (read) all the input, you must enclose the input within double quotes. Of course, once the input is within double quotes, it is a single literal field. You can then access the substrings "primary", "color", "is", and "red" with the strexplode or sub-string functions.

The second limitation of (read) is that you can't input parentheses unless they are within double quotes. Just as you can't assert a fact containing parentheses, you can't (read) parentheses directly except as literals.

The readline function is used to read multiple values until terminated by a carriage return. This function reads in data as a string. In order to assert the (readline) data, an (assert- string) function is used to assert the nonstring fact, just as input by (readline). A top-level example of (assert-string) follows.

CLIPS> (clear)

CLIPS> (assert-string "(primary color is red)")

<Fact-0>

CLIPS> (facts)

f-0 (primary color is red)

For a total of 1 fact.

CLIPS>

Notice that the argument of (assert-string) must be a string The following shows how to assert a fact of multiple fields from (readline).

CLIPS> (clear)

CLIPS> (defrule test-readline

(initial-fact)

=>

(printout t "Enter input" crlf)

(bind ?string (readline))

(assert-string (str-cat "(" ?string ")")))

CLIPS> (reset)

CLIPS> (run)

Enter input

primary color is red

CLIPS> (facts)

f-0 (initial-fact)

f-1 (primary color is r ed)

For a total of 2 facts.

CLIPS>

Since (assert-string) requires parentheses around the string to be asserted, the (str- cat) function is used to put them around ?string.

Both (read) and (readline) also can be used to read information from a file by specifying the logical name of the file as the argument. For more information, see the CLIPS Reference Manual.

Being Efficient

CLIPS is a rule-based language that uses a very efficient pattern-matching algorithm called the Rete Algorithm, devised by Charles Forgy of Carnegie-Mellon University for his OPS shell. The term Rete is Latin for net, and describes the software architecture of the pattern-matching process.

It is very difficult to give precise rules that will always improve the efficiency of a program running under the Rete Algorithm. However, the following should be taken as general guidelines that may help:

1. Put the most specific patterns in a rule first. Patterns with unbound variables and wildcards should be lower down in the list of rule patterns. A control fact should be put first in the patterns.

2. Patterns with fewer matching facts should go first to minimize partial matches.

3. Patterns that are often retracted and asserted, volatile patterns, should be put last in the list of patterns.

As you can see, these guidelines are potentially contradictory. A non-specific pattern may have few matches (see guidelines 1 and 2). Where should it go? The overall guideline is to minimize changes of the partial matches from one cycle of the Inference Engine to the next. This may require much effort by the programmer in watching partial matches. An alternative solution is simply to buy a faster computer, or an accelerator board. This is becoming more attractive since the price of hardware always goes down while the price of human labor always goes up. Because CLIPS is designed for portability, any code developed on one machine should work on another.

Other Features

The test conditional element provides a very powerful way by which to compare numbers, variables, and strings on the LHS. The (test) is used as a pattern on the LHS. A rule will only be triggered if the (test) is satisfied together with other patterns.

Many predefined functions are provided by CLIPS as shown in the following table.

Predefined Functions

Logical Arithmetic

not Boolean not / division

and Boolean and * multiplication

or Boolean or + addition

- subtraction

Comparison

eq equal (any type). Compares type and magnitude

neq not equal (any type)

= equal (numeric type). Compares magnitude

<> not equal (numeric type)

>= greater than or equal to

> greater than

<= less than or equal to

< less than

All the comparison functions except "eq" and "neq" will give an error message if they are used to compare a number and non-number. If the type is not known in advance, the "eq" and "neq" functions should be used. The eq function checks for the same magnitude and type of its arguments while the "=" function only checks the magnitude of its (numeric) arguments and doesn't care if they're integer or floating-point.

The logical functions of CLIPS are and, or, and not. They can be used in expressions as Boolean functions. In CLIPS, true and false are represented by the symbols TRUE and FALSE. Note that upper-case must be used for logical values in CLIPS.

In addition to all the predefined functions, you may write external functions or user-defined functions in C, Ada, or other procedural languages and link to CLIPS. These external functions are then used as you would any predefined function.

CLIPS also gives you the capability of specifying an explicit and conditional element, an or conditional element, and a not conditional element on the LHS. Th e absence of a fact is specified as a pattern on the LHS using the "not" conditional element.

The alteration of our information to conform to reality is called truth maintenance. That is, we try to maintain the state of our minds to contain only true information so as to minimize conflicts with the real world.

While people can do this fairly easily (practice makes perfect), it's difficult for computers because they don't normally know which pattern entities are logically dependent on other pattern entities. CLIPS has a feature to support truth maintenance which will internally tag those pattern entities which are logically dependent on others. If these other pattern entities are retracted, CLIPS will automatically retract the logically dependent ones. The logical conditional element uses the keyword logical around a pattern to indicate that the matching pattern entities provide logical support to the assertions on the RHS.

Although the logical support works for assertions, it does not reassert retracted facts. The moral is, if you lose something due to erroneous information, you can't get it back (like losing money on your stockbrokers advice.)

CLIPS has two functions to help with logical support. The dependencies function lists the partial matches from which a pattern entity receives logical support, or none if there is no support. The second logic function is dependents which lists all pattern entities which receive logical support from a pattern entity.

The connective constraint, uses "&", "|", or "~". Another type of field constraint is called a predicate constraint and is often used for pattern matching of more complex fields. The purpose of a predicate constraint is to constrain a field depending on the result of a Boolean expression. If the Boolean returns FALSE, the constraint is not satisfied and the pattern matching fails. You'll find that the predicate constraint is very useful with numeric patterns.

A predicate function is one which returns a FALSE or a non-FALSE value. The colon "" followed by a predicate function is called a predicate constraint. The ":" may be preceded by "&", "|", or "~" or may stand by itself as in the pattern (fact :(> 2 1)). It is typically used with the & connective constraint as "&"

Predicate Function Check if <arg> is

(evenp <arg>) even number

(floatp <arg>) floating-point number

(integerp <arg>) integer

(lexemep <arg>) symbol or string

(numberp <arg>) float or integer

(oddp <arg>) odd number

(pointerp <arg>) external address

(sequencep <arg>) multifield value

(stringp <arg>) string

(symbolp <arg>) symbol

There are often cases in which it's convenient to have values which are globally known in an expert system. For example, it is inefficient to have to redefine universal constants such as [[pi]]. CLIPS provides the defglobal construct so that values may be universally known to all rules.

Another type of useful function is random numbers. CLIPS has a random function which returns a "random" integer value. The random number function of CLIPS actually returns pseudorandom numbers, which means they are not truly random but are generated by a mathematical formula. For most purposes the pseudorandom numbers will be fine. Note that the random function of CLIPS uses the ANSI C library function rand which may not be available on all computers that do not adhere to this standard. For more information on all these topics, please see the CLIPS Reference Manual.

In addition to control facts to control the execution of programs, CLIPS provides a more direct way of control by the explicit assignment of salience to rules. The main problem associated with explicitly using salience while you were just starting to learn CLIPS is the tendency to overuse salience and write sequential programs. This overuse defea ts the whole purpose of using a rule-based language, which is to provide a natural vehicle for those applications best represented by rules. In the same way, procedural languages are best for strong control-oriented applications, while object-oriented languages are best for representing objects. CLIPS has keywords called declare salience which can be used to explicitly set the priority of rules.

Salience is set using a numeric value ranging from the smallest value of - 10000 to the highest of 10000. If a rule has no salience explicitly assigned by the programmer, CLIPS assumes a salience of zero. Notice that a salience of zero is midway between the largest and smallest salience values. A salience of zero does not mean that the rule has no salience but, rather, that it has an intermediate priority level.

CLIPS provides some procedural programming structures that can be used on the RHS. These structures are the while and if then else that also are found in modern high-level languages such as Ada, C, and Pascal.

Another useful function with (while) loops is the break which ends the currently executing (while) loop. The return function immediately ends the currently executing deffunction, generic function, method, or message-handler.

Any function may be called from the RHS, which greatly contributes to the power of CLIPS. Many other CLIPS functions are available that may return with numbers, symbols, or strings. These functions may be used for their return values or for their side-effects. An example of a function only used for its side-effect is (printout). The value returned by the (printout) is meaningless. The importance of (printout) is in its side-effect of output. In general, functions may have nested arguments if appropriate to your desired effect.

Before a file can be accessed for reading or writing, it must be opened using the open function. The number of files that can be opened at once is dependent on your operating system and hardware. When you no longer need to access a file, you should close it with the close function. Unless a file is closed, there is no guarantee that the information written to it will be saved.

The logical name of a file is how CLIPS identifies the file. The logical name is a global name by which CLIPS knows this file in all rules. Although the logical name could be identical to the filename, you may want to use something different. Another advantage of a logical name is that you can easily substitute a different filename without making major program changes.

The function to read data from a file is the familiar (read) or (readline). The only new thing that you have to do is to specify the logical name from which to read as the argument of (read) or (readline).

To (read) more than one field, you must use a loop. Even with (readline), a loop is necessary to read multiple lines. A loop can be written by having one rule trigger another or with a while-loop. The loop should not try to read past the end of file or the operating system will issue an error message. To help prevent this, CLIPS returns an EOF symbolic field if you try to read past the end of file (EOF).

The evaluation function, eval, is used for evaluating any string or symbol except the "def" type constructs such as defrule, deffacts, etc., as if entered at the top- level. The build function takes care of the "def" type constructs. The (build) function is the complement of (eval). The build function evaluates a string or symbol as if it were entered at the top-level and returns TRUE if the argument is a legal def-type construct such as (defrule), (deffacts), and so forth.

Chapter 8 Matters of Inheritance

The easiest way to obtain wealth is to inherit it; the second best way is to make it off the labor of others; marrying wealth is too much like work.

This chapter is an overview of object-oriented programming in CLIPS. Unlike rule- based programming in which you can just jump right in and write a rule without caring what else is in the system, object-oriented programming requires some essential background material.

How to be Objective

A key characteristic of good program design is flexibility. Unfortunately, the rigid methodology of structured programming techniques does not provide the needed flexibility for fast, reliable, and efficient changes. The object-oriented programming (OOP) paradigm. provides this flexibility.

The term paradigm comes from the Greek word paradeigma which means a model, example, or pattern. In computer science, a paradigm is a consistent, organized methodology for trying to solve a problem. Today, there are many programming paradigms such as OOP, procedural, rule-based, and connectionist. The term artificial neural systems, is a modern synonym for the older term connectionist.

Traditional programming is procedural because it emphasizes algorithms or procedures in solving problems. Many languages have been developed to support this procedural paradigm, such as Pascal, C, Ada, FORTRAN, and BASIC. These languages have also been adapted for objectoriented design (OOD) by either adding extensions or imposing a design methodology on the programmers. In contrast, new languages have been developed to provide OOP, which is not the same as OOD. You can do OOD in any language, even assembly language.

CLIPS provides three paradigms: rules, objects, and procedures. You will learn more about the objects in the CLIPS ObjectOriented Language (COOL) which is integrated with the rule and procedural based paradigms of CLIPS. CLIPS supports the procedural paradigm through generic functions, deffunctions, and user-defined external functions. Depending on the application, you can use rules, objects, procedures, or a combination.

Rather than imposing a single paradigm on the user, our philosophy is that a variety of specialized tools, a multiparadigm approach, is better than trying to force everyone to use a single general purpose tool. As an analogy, while you could use a hammer and nails for fastening everything, there are cases in which other fasteners are preferred. For example, imagine fastening your pants with a hammer and nails instead of a zipper. (NOTE: if anyone does use a hammer and nails on their pants, please contact the Guiness Book of World Records.)

The Class Stuff

In OOP a class is a template which describes the common characteristics or attributes of objects. Note that this use of the term template is not the same as a deftemplate as described in an earlier chapter. Here, the word template is used in the sense of a tool that is used to build objects having common attributes. As analogies, a straightedge is a template for drawing straight lines while a cookie-cutter is a curvacious template.

Classes of objects are arranged in a hierarchy or in a graph to describe the relationships of objects in a system. Each class is an abstraction of a real-world system or some other logical system that we are trying to model. For example, one abstract model of a real-world system might be an automobile. Another abstract model of a logical system could be financial instruments such as stocks and bonds, or complex numbers. The term abstraction refers to (1) the abstract descrip

Chapter 9 Meaningful Messages

It's always better to please your superiors than your subordinates.
-- Bowen

In this chapter you'll learn more about classes and objects called instances. You will see how to specify the attributes of classes using slots and how to send messages to objects.

The Birds and the BeesIn Chapter 1 you learned the basic ideas of inheritance. The reason that inheritance is so important in OOP is that inheritance allows the easy construction of customized software. By customized software, we don't mean that the software is built from scratch. Rather, it's more like taking a mass produced item and modifying it for a special application. The mass produced item can be considered a product of a software factory that quickly, economically, and reliably produces items of a general type that are meant to be easily customized.

The heart of the OOP paradigm is the creation of a class hierarchy to quickly, easily, and reliably produce software. Generally, this software is a modification of existing software so that programmers are not always "reinventing the loop."

Although in the past, people have tried to provide reusable code through such mechanisms as subroutine libraries, the pure OOP paradigm in languages such as Smalltalk carries the concept of reusable code to its logical conclusion by trying to build all the software in a system as reusable code. In Smalltalk, everything is an object, even the classes. In CLIPS, instances of the primitive types such as NUMBER, SYMBOL, STRING and so forth, as well as user-defined instances are objects. Classes are not objects in CLIPS. For example, the NUMBER 1, the SYMBOL Duck, the STRING "Duck", and the user-defined instance Duck are all objects.

The OOP paradigm is quite different from the subroutine library approach in which bits and pieces of subroutine code may or may not be used depending on the programmer's whim. The OOP paradigm encourages and supports modular code-- the message-handlers-- that can be easily modified and maintained. This feature of code maintainability is playing an increasingly important role as the size and cost of systems increase.

A class in OOP is like a software factory which has the design information about an object. In other words, a class is like a template which can be used to produce identical objects that are the instances of the class. The classic analogy is that a class is like the blueprint of a cow, and the object that produces milk, such as Elsie, is the instance.

The general syntax of an instance name is simply a symbol surrounded by brackets, [ ], as follows.

[<name>]

The brackets are not actually part of the instance name, which is a symbol, like Elsie. Brackets are used to surround an instance name if there is danger of ambiguity in using the name. This may occur in the (send) function and so brackets are used in a (send). In case of doubt, use brackets, since it doesn't hurt.

Some of the different types of objects in CLIPS are indicated in the following table.

Object Class

Dorky_Duck SYMBOL

"Dorky_Duck" STRING

1.0 FLOAT

1 INTEGER

(1 1.0 Dorky_Duck "Dorky_Duck") MULTIFIELD

<Pointer: 00AB12CD> EXTERNAL-ADDRESS

[Dorky_Duck] DUCK

The classes of SYMBOL, STRING, FLOAT, INTEGER, and MULTIFIELD have the same names as those you are familiar with from rule-based programming in CLIPS. These are called primitive object types because they are provided by CLIPS and automatically maintained as needed. These primitive types are mainly provided for use in generic functions. Two compound classes are NUMBER which is FLOAT or INTEGER, and LEXEME which is SYMBOL or STRING. The compound classes are provided for convenience if the type of number, or type of characters doesn't matter.

In contrast, userdefined object types are those that you define through user- defined classes. If you refer back to the predefined CLIPS classes of Fig. 1.7 in chapter 1, you'll see that primitive and user- defined classes are the top- level division of classes in CLIPS.

Two functions convert a symbol to an instance name, and vice versa. The symboltoinstancename converts a symbol to an instance name, as shown by the following.

CLIPS> (clear) ; Get rid of any old classes

CLIPS> (symbol-to-instance-name Dorky_Duck)

[Dorky_Duck]

CLIPS> (symbol-to-instance-name (sym-cat Dorky "_" Duck))

[Dorky_Duck]

CLIPS>

Notice how standard CLIPS functions such as (sym- cat), which concatenates items, can be used with the object system of CLIPS.

The opposite function, instance-name-to-symbol, converts an instance name to a symbol, as the following examples show.

CLIPS> (instance-name-to-symbol [Dorky_Duck])

Dorky_Duck

CLIPS> (str-cat (instance-name-to-symbol [Dorky_Duck]) " is a DUCK")

"Dorky_Duck is a DUCK"

CLIPS>

Dorky DuckThere is a difference between Nature and OOP. In Nature, objects are reproduced only from like objects, like the birds and the bees (the chicken and the egg are the exceptions to this rule.) However, in OOP instances are only created using the class template. In a pure OOP like Smalltalk, an instance of a specific class is created by sending the class a message. In fact, the heart of OOP involves sending different types of messages from one object to another, even from an object to itself.

In order to see how messages work, let's start by entering the following commands to create a user- defined DUCK class and check that it's entered. Notice that the role concrete descriptor is specified in order to allow direct instances of DUCK to be created. If the role is unspecified, CLIPS determines the role by inheritance.

If a class has role abstract no direct instances of it can be made. Abstract classes are defined for inheritance purposes only. For example, an abstract class called PERSON could be defined whose properties such as name, address, age, height, weight, and so on are inherited by concrete classes MAN and WOMAN. A direct instance of MAN could be a man-person called Harold, and a direct instance of WOMAN is a woman-person called Henrietta.

CLIPS> (defclass DUCK (is-a USER) (role concrete))

CLIPS> (describe-class DUCK)

==================================================================******************************************************************Concrete: direct instances of this class can be created.

Non-reactive: direct instances of this class cannot match defrule patterns.

Direct Superclasses: USER

Inheritance Precedence: DUCK USER OBJECT

Direct Subclasses:

--------------------------------------------------------------------------------

Recognized message-handlers:

init primary in class USER

delete primary in class USER

print primary in class USER

direct-modify primary in class USER

message-modify primary in class USER

direct-duplicate primary in class USER

message-duplicate primary in class USER

CLIPS>

******************************************************************==================================================================CLIPS>

Since classes are not objects in CLIPS, we can't send a message to make an object. Instead, the make-instance function is used to make an instance object. The basic syntax is as follows.

(make-instance [<instance-name>] of <class> <slot-override>)

Normally, you specify an instance-name. However, If you do not, CLIPS will generate one using the gensym* function. Slot values also can be specified.

Now that we have a duck factory, let's make some instances as follows, where the name of the instance is in brackets. Note the use of the "of" keyword to separate the instance name from the class name. You must include the "of" or a syntax error will result. Also, note that the brackets in the code mean an instance name, while brackets in the metasyntax such as for (make-instance) above, mean option.

CLIPS> (make-instance [Dorky] of DUCK)

[Dorky]

CLIPS> (make-instance [Elsie] of COW)

[PRNTUTIL1] Unable to find class COW.

CLIPS> (make-instance Dorky_Duck of DUCK)

[Dorky_Duck]

CLIPS> (instances)

[Dorky] of DUCK

[Dorky_Duck] of DUCK

For a total of 2 instances.

CLIPS>

After the instance is successfully created, CLIPS responds with the name of the instance. If it is not possible to create an instance, CLIPS responds with a FALSE. Also, like the (rules) and (facts) commands, CLIPS has an instances function to print out the instances of a class.

For the case of (make-instance), the brackets around the instance name is optional for a USER-defined class. As an example, let's create Dorky's cousin, Dorky_Duck, without brackets as follows.

CLIPS> (make-instance Dorky_Duck of DUCK)

[Dorky_Duck] ; Instance Dorky_Duck is made.

CLIPS>

There are two important rules about instances to keep in mind.

_Only one instance of the same name may be used in a module.

_A class cannot be redefined if instances of the class exist.

For example, let's make a clone of Dorky_Duck as follows (It's this evil clone that always gets Dorky_Duck in trouble because no one can tell them apart. Kids often have clones like this too, and some adults.)

CLIPS> (make-instance Dorky_Duck of DUCK)

[Dorky_Duck]

CLIPS> (instances)

[Dorky] of DUCK

[Dorky_Duck] of DUCK ; Still only one Dorky_Duck

For a total of 2 instances.

CLIPS>

Much Ado About InstancesIf a (reset) command is issued, all the instances in memory are deleted and an instance [initial-instance] is created, analogous to the fact, initial-fact.

CLIPS> (reset)

CLIPS> (instances)

[initial-object] of INITIAL-OBJECT

For a total of 1 instance.

CLIPS>

Just as (deffacts) defines facts, there is also a definstances to define instances when a (reset) is issued. The following (definstances) also illustrates the optional comment in double quotes after the instance name, DORKY_OBJECTS.

CLIPS> (definstances DORKY_OBJECTS "The Dorky Cousins"

(Dorky of DUCK)

(Dorky_Duck of DUCK))

CLIPS> (instances)

[initial-object] of INITIAL-OBJECT

For a total of 1 instance.

CLIPS> (reset)

CLIPS> (instances)

[initial-object] of INITIAL-OBJECT

[Dorky] of DUCK

[Dorky_Duck] of DUCK

For a total of 3 instances.

CLIPS>

The Disappearing DuckAlthough a (reset) will delete all instances except [initial-instance], it will also make new instances from (definstances). If you want to permanently delete an instance, the function unmakeinstance will delete one or all instances, depending on its argument. To delete all instances, use the "*".

The following examples illustrate the (unmake- instance) command.

CLIPS> (unmake-instance *) ; Delete all instances

TRUE

CLIPS> (instances) ; Check that all are gone

CLIPS> ; Restore the definstance

(definstances DORKY_OBJECTS "The Dorky Cousins"

(Dorky of DUCK)

(Dorky_Duck of DUCK))

CLIPS> (reset) ; Create new instances again

CLIPS> (instances) ; Check new instances created

[initial-object] of INITIAL-OBJECT

[Dorky] of DUCK

[Dorky_Duck] of DUCK

For a total of 3 instances.

CLIPS> (unmake-instance [Dorky]) ; Delete a specific instance

TRUE

CLIPS> (instances)

[initial-object] of INITIAL-OBJECT

[Dorky_Duck] of DUCK

For a total of 2 instances.

CLIPS>

Another way to delete a specific instance is to send a delete message. The general syntax of the (send) function is as follows.

(send [<instance-name>] <message>)

_Only one instance name can be specified in a command and it must be surrounded by brackets if it is a user-defined name.

For example, the following will make Dorky_Duck disappear.

CLIPS> (reset) ; Create new instances again

CLIPS> (instances) ; Check new instances created

[initial-object] of INITIAL-OBJECT

[Dorky] of DUCK

[Dorky_Duck] of DUCK

For a total of 3 instances.

CLIPS> (send [Dorky_Duck] delete)

TRUE

CLIPS> (instances)

[initial-object] of INITIAL-OBJECT

[Dorky] of DUCK

For a total of 2 instances.

CLIPS>

The "*" in a (send) will not work to delete all instances. The "*" only works with the (unmake) function. Another alternative is to define your own handler for delete that will accept the "*" and thus allow you to (send [instance-name] my_delete *) messages.

A (send) message is acted upon only by a target object which has an appropriate handler. CLIPS automatically provides handlers for print, init, delete and so on for each user-defined class. It's important to realize that the message (send [Dorky_Duck] delete) works only because this instance is a user-defined class. If you define classes which do not inherit from USER such as a subclass of INTEGER, you must also create appropriate handlers to carry out all desired tasks such as printing, creating, and deleting instances. It's much easier to define subclasses of USER and take advantage of system-supplied handlers.

What Did You Have For BreakfastThe (send) function is the heart of OOP operation since it is the only proper way for objects to communicate. According to the principle of object encapsulation, one object should only be allowed to access another object's data by sending a message.

For example, if someone wants to know what you had for breakfast, they'll generally ask you, i.e., send a message. An impolite alternative would be to yank open your mouth and peer down your throat. If the principle of object encapsulation is not followed, any object can fool around with the private parts of other objects, with potentially disastrous results.

One useful application of (send) is to print information about an object. So far all the examples of objects that you have seen have no structure. However, just as deftemplate gives structure to a rule pattern, the slots give an object structure. For both deftemplate and objects, a slot is a named location in which data can be stored. However, unlike deftemplate slots, objects obtain their slots from classes, and classes use inheritance. Thus, the information in object slots can be effectively inherited by objects of subclasses. An unbound slot is one that has no values assigned. All slots must be bound.

As a simple example, let's make an object with slots to hold personal information and then send messages to it. The following commands will first set up the CLIPS environment with the appropriate constructs. The slots named sound and age initially contain no data, i.e., nil values.

CLIPS> (clear)

CLIPS> (defclass DUCK (is-a USER) (role concrete)

(slot sound (create-accessor read-write))

(slot age (create-accessor read-write)))

CLIPS> (definstances DORK_OBJECTS

(Dorky_Duck of DUCK))

CLIPS> (reset)

CLIPS> (send [Dorky_Duck] print)

[Dorky_Duck] of DUCK

(sound nil)

(age nil)

CLIPS> (send [Dorky_Duck] put-sound quack)

quack

CLIPS> (send [Dorky_Duck] print)

[Dorky_Duck] of DUCK

(sound quack)

(age nil)

CLIPS>

Notice that the slots are printed in the order defined in the class. However, if the instance inherits slots from more than one class, the slots from the more general classes will be printed first.

Just as slots describe instances, facets describe slots. A special facet is needed in this example, createaccessor, which tells CLIPS to create put- and get- handlers for the class. If you define your own handlers, then you won't use the create-accessor facet. The facet types for create accessor are read- write, read, and write. Facets are described in more detail in the next chapter.

Whether you use the handlers created by CLIPS or else define your own, you can also set the slot access to read-write, read-only, and initialize-only. The read-write access is the default and so it was not necessary to specify it in this example.

The value of a slot is changed using the put- message. Notice the dash, "-", at the end of "put-". The dash is an essential part of the message syntax since it separates the "put" from the slot name. Only one "put-" is allowed in a (send). Thus, to change multiple slots or the same slot of many instances, you must send multiple messages. Instead of doing this manually, it's possible to write a function to do multiple sends, or use the modify-instance function.

The value of a slot can be set by a slot-override in a make-instance. As an example,

CLIPS> (make-instance Dixie_Duck of DUCK (sound quack) (age 2))

[Dixie_Duck]

CLIPS> (send [Dixie_Duck] print)

[Dixie_Duck] of DUCK

(sound quack)

(age 2)

CLIPS>

The complementary message to "put-" is get- which gets the data from a slot, as shown in the following example. If a put- is successful it returns the new value, while if get- is successful it returns the appropriate data. If the put- or get- does not succeed, an error message will be returned. The following examples show how this works.

CLIPS> (send [Dorky_Duck] put-color white) ; No slot color

[MSGFUN1] No applicable primary message-handlers found for put-color.

FALSE

CLIPS> (send [Dorky_Duck] get-age)

nil

CLIPS> (send [Dorky_Duck] put-age 1); Value put in age

1

CLIPS> (send [Dorky_Duck] get-age); Check value is correct

1

CLIPS>

In contrast to the put- message, the get- message returns the value of a slot. Since the value of get- is returned, it can be used by another function, assigned to a variable, and so forth. In contrast, a value that is printed out cannot be used by another function, assigned to a variable, and so forth because the value goes to the standard output device. One way of getting around this problem is to print out to a file and then read in the data from the file. While this is not an elegant solution, it does work. Another way is to write your own print message-handler that also returns values.

A very important point about slots is that you cannot modify the slots of a class by adding slots, deleting slots, or changing the characteristics of slots. The only way to change a class is to (1) delete all instances of the class, and (2) use a (defclass) with the same class name and the desired slots. This situation is analogous to modifying a rule by loading in a new rule with the same name.

Class EtiquetteNow that you've learned aqbout slots and instances, it's time to discuss class etiquette. The term etiquette refers to a set of guidelines for doing something.

In contrast to standard procedural programming, the OOP paradigm is class oriented. Each object is intrinsically related to a class, and that class is part of a class hierarchy. Rather than concentrating on actions first and foremost, the OOP programmer considers the overall class hierarchy or class architecture, and how messages will be sent between objects. Thus, actions in customary procedural programs are performed explicitly, while the actions are performed implicitlty in OOP. In either case, the end result is the same. However, the OOP system can be more easily verified, validated, and maintained.

The proper use of classes is summarized in the following three rules.

Rules of Class Etiquette
1. The class hierarchy should be in specialized logical increments using is-a links.
2. A class is unnecessary if it has only one instance.
3. A class should not be named for an instance and vice versa.

The first rule discourages the creation of a single class for your application. If a single class is adequate, then you probably don't need OOP. By creating classes in increments, you can more easily verify, validate, and maintain your code. In addition, incremental class hierarchies can be easily put in class libraries to greatly facilitate the creation of new code. This concept of class libraries is analogous to subroutine libraries for actions. Only is-a links can be used since this is the only relationship that Version 6.0 of CLIPS supports.

The second rule encourages the idea that classes are intended as a template to produce multiple objects of the same kind. Of course you can start out with zero or one instance. However, if you'll never need more than one instance in a class, you should consider modifying its superclass to accomodate the instance rather than defining a new subclass. If all your classes only have one instance, it is probable that your application is simply not well-suited to OOP and that coding in a procedural language may be best.

The third rule means that classes should not be named after instances and vice versa, to eliminate confusion.

Other FeaturesThere are a number of useful predicate functions for slots. If you use these predicate functions to test for appropriate values to functions, your program will be more robust against crashes. In general, if a function does not return TRUE, it returns FALSE.

Function Meaning

classslotexistp Returns TRUE if the class slot exists

slot-existp Returns TRUE if the instance slot exists

slot-boundp Returns TRUE if the specified slot has a value

instance-address Returns the machine address at which the specified instance is stored.

instance-name Returns the name given an address and vice versa

instancep Returns TRUE if its argument is an instance

instanceaddressp Returns TRUE if its argument is an instance address

instance-namep Returns TRUE if its argument is an instance name

instance-existp Returns TRUE if instance exists

list-definstances Lists all the definstances

ppdefinstances Pretty-prints the definstance

watch instances Allows you to watch instances being created and deleted.

unwatch instances Turns off watching instances.

save-instances Save instances to a file

load-instances Load instances to a file

undefinstances Deletes the named definstance.

Chapter 10 Fascinating Facets

If you want to have class, then act, dress, and talk like your friends.

In this chapter you'll learn more about slots and how to specify their characteristics by using facets. The use of facets is good software engineering because there is a greater chance of CLIPS flagging an illegal value rather than risking a runtime error or crash. There are many types of facets that may be used to specify slots, as summarized in the following table.

Facet Name Description

default and default-dynamic Set initial values for slots
cardinality Number of multifield values
access type Read-write, read-only, initialize-only access
storage Local slot in instance or shared slot in class
propagation Inherit, or no inherit slots
source composite or exclusive inheritance
documentation Documentation of slots
overridemessage Indicate message to send for slot override
create- accessor Create put- and get- handlers
visibility Public, or private to defining class only
reactive Changes to a slot trigger pattern- matching

For reasons of space, we'll only describe a few facets in more detail in the rest of this chapter. For more details, see the CLIPS Reference Manual.

A Slot Named DefaultThe default facet sets the default value of a slot when an instance is created or initialized, as shown in the following example.

CLIPS> (clear)

CLIPS> (defclass DUCK (is-a USER)(role concrete)

(slot sound (create-accessor read-write)(default quack))

(slot ID (create-accessor read-write))

(slot sex (create-accessor read-write)(default male)))

CLIPS> (make-instance Dorky_Duck of DUCK)

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] print)

[Dorky_Duck] of DUCK

(sound quack)

(ID nil)

(sex male)

CLIPS>

As you can see, the default values for slot sex and slot sound were set by the default facet values. Following the default keyword can be any valid CLIPS expression that does not involve a variable. For example, the default expression of the sound slot is the symbol quack. Functions may be used in the facet expression as will be shown in the next example.

This default facet is a static default because the value of its facet expression is determined when the class is defined and never changed unless the class is redefined. For example, let's set the default value of slot ID to the (gensym*) function which returns a new value not in the system everytime it's called.

CLIPS> (clear)

CLIPS> (defclass DUCK (is-a USER)(role concrete)

(slot sound (create-accessor read-write)(default quack))

(slot ID (create-accessor read-write)(default (gensym*)))

(slot sex (create-accessor read-write)(default male)))

CLIPS> (make-instance [Dorky_Duck] of DUCK) ; Dorky_Duck #1

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] print)

[Dorky_Duck] of DUCK

(sound quack)

(ID gen1)

(sex male)

CLIPS> (make-instance [Dorky_Duck] of DUCK) ; Dorky_Duck #2

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] print)

[Dorky_Duck] of DUCK

(sound quack)

(ID gen1)

(sex male)

CLIPS>

As you can see, the ID is always gen1 since (gensym*) is only evaluated once, and not again when the second instance is created. Note that the (gensym*) values may be different on your computer if you have already called the (gensym*) since it increments by one each time it is called, and is not reset by a (clear). The (gensym*) function is reset to its starting value only if you restart CLIPS.

Now suppose that we want to keep track of the different Dorky_Duck instances that have been created. Rather than using the static default, we can use the facet called default dynamic which will evaluate its facet expression every time a new instance is created. Notice the difference between the following example and the previous.

CLIPS> (clear)

CLIPS> (defclass DUCK (is-a USER)(role concrete)

(slot sound (create-accessor read-write)(default quack))

(slot ID (create-accessor read-write)

(default-dynamic (gensym*)))

(slot sex (create-accessor read-write)(default male)))

CLIPS> (make-instance [Dorky_Duck] of DUCK) ; Dorky_Duck #1

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] print)

[Dorky_Duck] of DUCK

(sound quack)

(ID gen2)

(sex male)

CLIPS> (make-instance [Dorky_Duck] of DUCK) ; Dorky_Duck #2

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] print)

[Dorky_Duck] of DUCK

(sound quack)

(ID gen3) ; Note ID is different from Dorky_Duck #1

(sex male)

CLIPS>

In this example which uses dynamic default, the ID of the second instance, gen3, is different from the first instance, gen2. In contrast, for the previous example of static default, the ID values were the same, gen1, since the (gensym*) was only evaluated once when the class was defined rather then for every new instance in the case of dynamic default.

Cardinal PropertiesThe cardinality of a slot refers to one of two types of fields that a slot can hold: (1) single-field, or (2) multifield. The term cardinality refers to a count. A bound single- field slot contains only one field, while a bound multifield slot may contain zero or more fields. The bound single-field slot and the bound multifield slot each contain one value. However, the one multifield value may have multiple fields in it. For example, (a b c) is a single multifield value with three fields. The empty string "" is a single-field value, just as "a b c" is. In contrast, an unbound slot has no value.

As an analogy to single and multifield variables, think of a slot as your mailbox. Sometimes you may find a single piece of junk-mail that doesn't have an envelope. Instead, an address label has just been stuck on a folded piece of paper addressed to "Resident." Other times you may find an envelope with multiple ads in it. The single piece of junk mail without an envelope is like a single-field value while the envelope with multiple ads is like the multifield value. If the junk-mail distributor slips up and mails you an envelope with nothing inside, this corresponds to the empty multifield variable. (Come to think of it, if the junk-mail envelope is empty, have you really received junk-mail?)

A multiple facet with keyword multislot, is used to store a multifield value as shown in the following example.

CLIPS> (clear)

CLIPS> (defclass DUCK (is-a USER)(role concrete)

(multislot sound (create-accessor read-write)

(default quack quack)))

CLIPS> (make-instance [Dorky_Duck] of DUCK)

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] print)

[Dorky_Duck] of DUCK

(sound quack quack)

CLIPS>

A multifield value can be accessed using get- and put- as shown in the following examples, which shows how to keep track of quacks.

CLIPS> (send [Dorky_Duck] put-sound quack1 quack2 quack3)

(quack1 quack2 quack3)

CLIPS> (send [Dorky_Duck] get-sound)

(quack1 quack2 quack3)

CLIPS>

Standard CLIPS functions such as nth$ to get the nth field of a multislot value can be used. The following example shows how to pick a certain quack.

CLIPS> (nth$ 1 (send [Dorky_Duck] get-sound))

quack1

CLIPS> (nth$ 2 (send [Dorky_Duck] get-sound))

quack2

CLIPS> (nth$ 3 (send [Dorky_Duck] get-sound))

quack3

CLIPS>

Other Features

CLIPS has several multifield slot functions as shown in the following table.

Function Meaning

slot-replace$ Replace the specified range
slot-insert$ Insert the specified range
slot-delete$ Delete the specified range

A multifield slot with no values, e.g., the empty multifield value (), may be assigned to a slot with a (multiple) facet. Note that there is a difference between a slot with an empty multifield value () and an unbound slot. If you think of an empty multifield value as analogous to an empty bus, you can see there is a difference between no people (unbound slot) and a bus with no people (empty multifield value, () ).

A storage facet defines one of two places that a slot value is stored: (1) in an instance, or (2) in the class. A slot value stored in the instance is called local because the value is only known to the instance. Thus, different instances may exist that have different local slot values. In contrast, a slot value stored in a class is called shared because it is the same for all instances of the class.

A local value is specified by the local facet, which is the default for a slot. A shared value is specified by the shared facet and all instances with this slot type will have their slot value automatically changed if one changes. An access facet defines one of three types of access for a slot, as summarized in the following table.

Another way to set the instance values is with the initialize-instance function. An (initialize-instance) can be called at any time to reset the default values and retain values in non-(default) slots.

A (reset) can be thought of as a coldinitialization since all values in non- (default) slots are cleared, while a (initialize- instance) can be considered a warminitialization since non-(default) values are retained. Of course, only (definstances) can be cold- initialized since non-(definstances) will simply be deleted. Also, slot- overrides may be used in (initialize-instance) as the last example shows.

Two predicate functions are designed for use with the access facets. Both these predicate functions return an error message if the specified slot or instance does not exist. The slot-writablep is a predicate function which returns TRUE if a slot is writable and FALSE if it is not. The slot-initablep predicate function returns TRUE if the slot is initializable and FALSE if it is not. The term initializable means that it is not read-only.

The inherit facet, which is the default, specifies that indirect instances of a class may inherit this slot from the class. As you recall, the indirect instances of a class are the instances of its subclasses, while the direct instances are those defined specifically for the class. The indirect instances of a class are direct instances of the subclasses in which they are defined. For example, [Dorky_Duck] is a direct instance of DUCK and an indirect instance of USER which is the superclass of DUCK. The no-inherit facet specifies that only a direct instance has the class slot.

It's important to realize that the (no-inherit) facet only prohibits inheritance from the class and not from its superclasses. This means that an instance may still inherit from superclasses of the (no-inherit) class.

The composite facet. facet states that facets which are not explicitly defined in the highest precedence class take their facets from the next higher precedence class. If the facet is not explicitly set in the next higher precedence class and it is composite too, CLIPS tries the next higher and so on until the facet is defined or there are no more classes. If the next higher class is not composite, CLIPS does not check further. The opposite to the composite facet is the exclusive facet, which is the default. For more information, see the CLIPS Reference Manual.

Chapter 11 Handling Handlers

There are two steps in learning how to use a shovel: (1) finding which part is the handle, and (2) what to do with the handle.

Handlers are essential in OOP because they support object encapsulation. The only proper way that objects can respond to messages is by having an appropriate handler to receive the message and take appropriate action. In this chapter you'll learn the how messages are interpreted by objects. You'll see how to modify existing message- handlers, and how to write your own.

Your Primitive Self

So far you've learned about the static structure of classes through the inheritance hierarchy and slots. However, the dynamic part of an object is determined by its messagehandlers, or handlers for short, which receive messages and performs actions in response. The handlers are responsible for the dynamic properties of an object, which determine its behavior. You've already used one handler many times -- the print in a (send).

Polymorphism is one of the five generally accepted features of a true OOP language. For example, the same type of message, (send <instance-name> print), may have different actions depending on the class of the object which receives it. In addition to egg-of and color, DUCK objects print out sound, ID, and age, while DUCKLING objects only print out sound and age.

In languages without polymorphism, you would have to define one function, (send- egg- print) for egg types and another function, (send-duckling-print) for the duckling type. However, in OOP, no matter how many classes are defined, the same message, (send <instance-name> print), will print the object slots. This greatly improves the efficiency of program development since you do not have to define new functions for every new type.

Polymorphism can be carried to extremes by having the same message do completely different things. For example, a print message-handler could be defined that would print objects of a certain class and delete objects of another class. Another extreme possibility would be not having the print handler print anything. Instead, it would delete objects of one class, save objects of another class, add objects of another class, and so forth.

This extreme use of polymorphism would create a programmer's Tower of Babel and make it very hard to understand the code since everything would be run-time dependent. Defining message-handlers of the same name in different classes that do completely different things goes against the Principle of Least Astonishment.

Another example of polymorphism could be defined using a message-handler for "+". If a message for "+" is sent to strings or symbols, i.e., LEXEME objects, they will be concatenated because of a handler defined for the LEXEME class. If the "+" is sent to ordinary numbers, the result is addition because of the predefined system handler for addition of numbers. If the "+" is sent to complex numbers, defined as a subclass of USER called COMPLEX, a handler defined for the COMPLEX class will do complex number addition. Thus, the "+" does related types of operations that matches our intuition, and does not surprise us.

In addition to the predefined handlers such as print, you may define your own handlers. Let's start by writing a handler to add numbers through messages.

As you can see from Fig. 1.7 of chapter 1, the class NUMBER has subclasses INTEGER and FLOAT. Since these are predefined classes, it would seen natural to do numeric calculations by sending messages to numbers. Let's try it as follows.

CLIPS> (clear)

CLIPS> (send 1 + 2)

[MSGFUN1] No applicable primary message-handlers found for +.

FALSE

CLIPS>

Well, as you can see, this example didn't work. The reason why is implied in the error message. Let's check it out by obtaining more information about the INTEGER class since that was the target object of the print message.

CLIPS> (describe-class INTEGER)

==================================================================

******************************************************************Abstract: direct instances of this class cannot be created.

Direct Superclasses: NUMBER

Inheritance Precedence: INTEGER NUMBER PRIMITIVE OBJECT

Direct Subclasses:

******************************************************************==================================================================CLIPS>

The problem is that the INTEGER class has no handler for "+". In fact, it has no handlers at all since none are listed. As you recall, the USER class and its subclasses always have print, delete, and other handlers automatically defined by CLIPS. If we want to send print messages to an object like 1 of the INTEGER class, we'll have to make our own print handler.

Before writing this handler, let's answer a question that you may have concerning how INTEGER can have instances. Since INTEGER is an abstract class, you may wonder how it can have instances such as 1, 2, 3, etc. Although you cannot make direct instances of an abstract class, you can make use of existing instances. For the case of the predefined system class INTEGER, all the integers up to the maximum allowed are available as objects. Likewise, strings and symbols are available for the system defined abstract classes STRING and SYMBOL, and so forth for the other predefined classes.

Shown following is the definition of a handler for the NUMBER class that will handle addition by messages. The handler is defined for NUMBER rather than INTEGER because we would also like to handle FLOAT objects too. Instead of defining the same handler for FLOAT and for INTEGER, it's easier to just define a handler for the superclass NUMBER. If a handler for a message is not defined in the class of the object, CLIPS tries all the handlers in the inheritance precedence list. Since "+" is not defined for INTEGER, CLIPS tries NUMBER next, finds the applicable handler, and returns the result of 3.

CLIPS> (defmessage-handler NUMBER + (?arg) ; Argument of handler

(+ ?self ?arg)) ; Function addition of handler

CLIPS> (send 1 + 2)

3

CLIPS> (send 2.5 + 3)

5.5

CLIPS> (send 2.5 + 2.6)

5.1

CLIPS> (describe-class NUMBER)

==================================================================******************************************************************Abstract: direct instances of this class cannot be created.

Direct Superclasses: PRIMITIVE

Inheritance Precedence: NUMBER PRIMITIVE OBJECT

Direct Subclasses: INTEGER FLOAT

------------------------------------------------------------------Recognized message-handlers:

+ primary in class NUMBER

******************************************************************==================================================================CLIPS>

The variable ?self is a special variable in which CLIPS stores the active instance. The ?self is a reserved word that cannot be explicitly included in a handler argument, nor can it be bound to a different value. The active instance is the instance to which the message was sent. In our example, all the predefined classes such as NUMBER, INTEGER, and FLOAT are all subclasses of the PRIMITIVE class. This is in contrast to USER, which is the other main subclass of OBJECT.

As another example, lets write a handler to concatenate strings, symbols or both.

CLIPS> (defmessage-handler LEXEME + (?arg) ; Argument of handler

(sym-cat ?self ?arg)) ; Function concatenation of handler

CLIPS> (send Dorky_ + "Duck") ; SYMBOL + STRING

Dorky_Duck ; SYMBOL result

CLIPS>

Notice that the handler is defined for the LEXEME class since that is a superclass of both SYMBOL and STRING. In this case, the handler returns a SYMBOL since (sym- cat) is used.

This example also illustrates why brackets may be necessary in a (send). As shown in this example, the message goes to the SYMBOL Dorky_ without brackets. With brackets, the message goes to an object [Dorky_] of a user-defined class. Here we assume that [Dorky_] could be an object of a user-defined class, such as DUCK.

Make 'Em Pay Through the Nose

The real utility of handlers is with subclasses of USER since you can define instances of these classes. To see how handlers work in this case, let's first set up the environment as follows.

(clear)

(defclass DUCKLING (is-a USER)(role concrete)

(slot sound (create-accessor read-write)(default qua))

(slot age (create-accessor read-write)))

(defclass DUCK (is-a DUCKLING)

(slot sound (create-accessor read-write)(default quack)))

(definstances DUCKY_OBJECTS

(Dorky_Duck of DUCK (age 2))

(Dinky_Duck of DUCKLING (age .1)))

(reset)

As a simple example, let's write a handler that will print out the slots of the active instance. We can make use of the ppinstance function to print out the slots of the active instance. This function does not return a value and is used only for its side-effect of printing to the standard device. Also, it can only be used from within a handler since only there is the active instance known. Shown following is a USER-defined handler called print- slots that prints out the slots of the active instance using (ppinstance).

CLIPS> (defmessage-handler USER print-slots ()

(ppinstance))

CLIPS> (send [Dorky_Duck] print-slots)

[Dorky_Duck] of DUCK

(age 2)

(sound quack)

CLIPS>

Although the handler could be defined just for DUCK in this case, a handler defined for USER will be called for all subclasses of USER, not just DUCKLING and DUCK. Thus, the handler print-slots will work for all subclasses that we may define of USER.

Of course it's possible to get carried away and define all your message handlers as USER handlers. However, it's good style and improves efficiency to define handlers as close as possible to the class or classes for which they are intended. Efficiency is improved because CLIPS does not have to keep searching through a lot of classes to find the applicable handler.

Getting Around

Let's examine message-handlers in more detail now. We'll define a handler to print out a header when an object receives a message to print itself. The message-handler is defined using a defmessage-handler construct as follows.

CLIPS> (defmessage-handler USER print before ()

(printout t "*** Starting to print ***" crlf))

CLIPS> (send [Dorky_Duck] print)

*** Starting to print ***

[Dorky_Duck] of DUCK

(age 2)

(sound quack)

CLIPS>

The reason that a header is printed rather than a trailer at the end has to do with the handler type. A before type handler is used before the print message. To make a trailer, use the after type handler as shown in the following example.

CLIPS> (defmessage-handler USER print after ()

(printout t "*** Finished printing ***" crlf))

CLIPS> (send [Dorky_Duck] print)

*** Starting to print ***

[Dorky_Duck] of DUCK

(age 2)

(sound quack)

*** Finished printing ***

CLIPS>

The general format of a message-handler is as follows.

(defmessage-handler <class-name> <message-name> [handler-type] [comment]

(<parameters>* [wildcard-parameter])

<action>*)

While there may be multiple actions in a handler, only the value of the last action is returned. Notice that this is just like a (deffunction).

Since [Dorky_Duck] is of class DUCK, a subclass of USER, we can take advantage of the print handler that is predefined by CLIPS for the USER class. All subclasses of USER can take advantage of the handlers of USER, which saves you the trouble of writing handlers for every class that you define. Notice how the concept of inheritance from USER to its subclass DUCK simplifies program development by allowing reuse of existing code, i.e., the print handler of USER.

The empty parentheses () that follow the before handler type mean that there are neither parameters nor a wildcard parameter. In other words, the header handler takes no arguments and so the parentheses are empty, but required. Note that while multiple parameters may be used, there can be only one wildcard.

Primary Considerations

As you can see, the trailer handler is the same as the header handler except that an after handler type is used, and the action text is different. Thus, a before handler type does its task before the primary type handler, and an after handler does its task after the primary handler. A primary is intended to do the major task. An around handler type is intended to set up the environment for the rest of the handlers. The before and after types are intended for minor tasks such as initializing variables or printing, while the primary does the major task.

The following table summarizes the handler types.

Handler Type Class Role Return Value

around Set up environment for other handlers Yes before Auxilliary work before primary No
primary Perform major task of message Yes
after Auxilliary work after primary No

Summary of Message-Handler Types

The handler types are listed in the order that they are normally called during execution of a message. Depending on the handler type, CLIPS knows when to execute it. That is, an around handler starts before any before handlers. A before handler is executed before any primary handlers, which are followed by the after handlers. The exception to this sequential handler execution is the around type handler. If an around handler is defined, it will start execution before any of the others, perform specified actions, and then complete its actions after all the other handler types have finished. You'll see a detailed example of these handlers execution soon.

The class role describes the intended purpose of each type. The column headed "Return Value" describes whether the handler type is generally intended for a return value or simply to provide a useful side-effect such as printing. This consideration will depend on the handler. For example, many user-defined primary handlers may be written to return a value as the result of some numeric calculation or string operation. An exception to returning a useful return value is a print primary handler whose main task is the side-effect of printing, and does not have a return value.

The following table lists the predefined primary handlers of USER. By inheritance, these are available for all subclasses of USER.

Primary Type Class Role

init Initialize an instance
delete Delete an instance
print Print the object
direct-modify Directly modifies slots
message-modify Modifies slots using put- messages
direct-duplicate Duplicates instance without put- message
message-duplicate Duplicates an instance using messages

Predefined USER Message-handlers of Primary Type

These primary handlers are predefined and cannot be modified unless you change the source code of CLIPS. However, you may define the before, after and around handler types for these primaries. You've already seen an example of changing the before and after handler types for the USER print handler. Now let's look at some examples of defining the before and after handler types for the init primary handler.

CLIPS> (defmessage-handler USER init before ()

(printout t "*** Starting to make instance ***" crlf))

CLIPS> (defmessage-handler USER init after ()

(printout t "*** Finished making instance ***" crlf))

CLIPS> (reset)

*** Starting to make instance ***

*** Finished making instance ***

*** Starting to make instance ***

*** Finished making instance ***

*** Starting to make instance ***

*** Finished making instance ***

CLIPS> (make-instance Dixie_Duck of DUCK (age 1))

*** Starting to make instance ***

*** Finished making instance ***

[Dixie_Duck]

CLIPS> (instances)

[initial-object] of INITIAL-OBJECT

[Dorky_Duck] of DUCK

[Dinky_Duck] of DUCKLING

[Dixie_Duck] of DUCK

For a total of 4 instances.

CLIPS>

The Power of Belief

The self parameter is useful because it can be used to read a slot value in the form

?self:<slot-name>

However, it cannot be used to write a slot value. The "?self:" notation is more efficient than sending messages but can only be used from within a handler on its active instance. In contrast, the dynamic-get- and dynamic-put- functions can be used from within a handler to read and write a slot value of the active instance. Although you can use messages from inside a handler, such as the following, it's not efficient.

(send ?self dynamic-get-<slot>)

(send ?self dynamic-put-<slot>)

As an example of dynamic-get-, let's change our example as follows.

CLIPS> (defmessage-handler USER print-age primary ()

(printout t "*** Starting to print ***" crlf

"Age = " (dynamic-get age) crlf

"*** Finished printing ***" crlf))

CLIPS> (send [Dorky_Duck] print-age)

*** Starting to print ***

Age = 2

*** Finished printing ***

CLIPS>

The ?self:age can only be used in a class and its subclasses which inherit the slot age. The ?self:<slot-name> is evaluated in a static way through inheritance. This means that if a subclass redefines a slot, a superclass message-handler will fail if it tries to directly access the slot using ?self:<slot-name>.

In contrast, the dynamic-get- and dynamic-put- can be used by superclasses and subclasses because these check slots dynamically. The following example would not work if DUCK is changed to USER.

CLIPS> (defmessage-handler DUCK print-age primary ()

(printout t "*** Starting to print ***" crlf

"Age = " ?self:age crlf

"*** Finished printing ***" crlf))

CLIPS> (send [Dorky_Duck] print-age)

*** Starting to print ***

Age = 2

*** Finished printing ***

CLIPS>

As an example of using a dynamic-put- function in a handler, suppose we want to help Dorky_Duck regain some of his youth. The following example shows how his age can be changed using a handler. This example also illustrates how a value can be passed to a handler through the ?change variable.

CLIPS> (clear)

CLIPS> (defclass DUCK (is-a USER) (role concrete)

(slot sound (create-accessor read-write)(default quack))

(slot age (create-accessor read-write)))

CLIPS> (defmessage-handler DUCK lie-about-age (?change)

(bind ?new-age (- ?self:age ?change))

(dynamic-put age ?new-age)

(printout t "*** Starting to print ***" crlf

"I am only " ?new-age crlf

"*** Finished printing ***" crlf))

CLIPS> (make-instance [Dorky_Duck] of DUCK (age 3))

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] lie-about-age 2)

*** Starting to print ***

I am only 1

*** Finished printing ***

CLIPS>

As you can see, Dorky_Duck's belief is so strong that the changed age is put in his age slot. Notice how the handler uses the variable ?new-age to store the changed age, which is then put into the age slot of the instance.

The Truthful Daemon

A daemon is a handler which executes whenever some basic action like initialization, deletion, get, or put is performed on an instance. A rule cannot be considered a daemon because it's not certain that it will be executed just because its LHS patterns are satisfied. The only thing that is certain is that a rule will become activated when its LHS is satisfied -- not that it will execute.

There is no explicit keyword for daemon since it's just a concept. The before and after handlers that printed strings can be considered print daemons. These handlers waited for a (send [Dorky_Duck] print-age) message to trigger their action. First the before handler printed its string, then the primary handler printed, and finally the after handler printed. One daemon is the before handler which waits for a print message. The second daemon is the after handler that waits for the print primary to finish printing.

Printing is not considered a basic action because there is no return value associated with a (send <instance> print). The print message is only sent for the side- effect of printing. In contrast, a (send <instance> get-<slot>) message will return a value that may be used by other code. Likewise, the initialization, deletion, and put all have an effect on an instance and so are considered basic actions like get.

Daemons are easily implemented using before and after handlers since these will be executed before and after their primary handler. Implementing daemons like this is called declarative implementation because no explicit actions on the part of the handler is necessary for it to be executed. That is, CLIPS will always execute a before handler before its primary and will always execute an after handler after its primary. In a declarative daemon implementation, the normal operation of CLIPS will cause the daemons to be activated when their time has come. Thus, the declarative implementation is implicit in the normal operation.

The opposite of implicit execution is the imperative implementation in which the actions are explicitly programmed. The around handler is very convenient to use for imperative daemons. The basic idea of the around handler is as follows.

1. Start before any other handlers.

2. Call the next handler using either call-next-handler to pass the same arguments or overridenexthandler to pass different ones.

3. Continue execution when the last handler finishes.

4. After any other around, before, primary, or after handlers finish, the around handler resumes execution.

The keyword call-next-handler is used to call the next handler(s). A handler is said to be shadowed by a shadower if it must be called from the shadower by a function such as call-next-handler. The call- next- handler may be used multiple times to call the same handler(s).

A predicate function called next-handlerp is used to test for the existence of a handler before the call is made. If no handler exists, then next-handlerp will return FALSE.

The following example illustrates the around handler through a truthful daemon that tells on Dorky_Duck whenever he lies about his age.

CLIPS> (defmessage-handler DUCK lie-about-age around (?change)

(bind ?old-age ?self:age)

(if (next-handlerp) then

(call-next-handler))

(bind ?new-age ?self:age)

(if (<> ?old-age ?new-age) then

(printout t "Dorky_Duck is lying!" crlf

"Dorky_Duck is lying!" crlf

"He's really " ?old-age crlf)))

CLIPS> (make-instance [Dorky_Duck] of DUCK (age 3))

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] lie-about-age 1)

*** Starting to print ***

I am only 2

*** Finished printing ***

Dorky_Duck is lying!

Dorky_Duck is lying!

He's really 3

CLIPS>

Although Dorky_Duck may still lie about his age, the daemon tells the truth.

Notice the ?change argument. Although the around handler does not use ?change, the lie-about-age primary that is called by the call-next-handler does need it to change the age. Thus, ?change must be passed to the primary by the around handler. An error message will occur if you leave out the ?change.

The call-next-handler always passes the arguments of the shadower to the shadowed handler. It's possible to pass different arguments to a shadowed handler by use of the override- next- handler function as shown in the following example.

CLIPS> (defmessage-handler DUCK lie-about-age around (?change)

(bind ?old-age ?self:age)

(if (next-handlerp) then

(override-next-handler (/ ?change 2))); Divide age in half!

(bind ?new-age ?self:age)

(if (<> ?old-age ?new-age) then

(printout t "Dorky_Duck is lying!" crlf

"Dorky_Duck is lying!" crlf

"He's really " ?old-age crlf)))

CLIPS> (make-instance [Dorky_Duck] of DUCK (age 3))

[Dorky_Duck]

CLIPS> (send [Dorky_Duck] lie-about-age 1)

*** Starting to print ***

I am only 2.5

*** Finished printing ***

Dorky_Duck is lying!

Dorky_Duck is lying!

He's really 3

CLIPS>

_ It's important to keep in mind that the return value of call- next- handler and override- next- handler is that of the shadowed handlers.

Shown following are the rules of message dispatch. However, note the following prerequisite to any message handling:

_ There must be at least one applicable primary handler .

Rules of Message-handler Precedence
1. All the around handlers start execution. Then the before, primary, and after

handlers start and finish, followed by completion of the arounds execution.

2. The around, before, and primary handlers are called in order of highest
precedence class to lowest.
3. The after handlers are called from lowest precedence class to highest.
4. Each around handler must explicitly call the next shadowed handler.
5. Higher precedence primaries must explicitly call lower precedence (shadowed)

primaries if they are to execute.

Since only around and primary handlers can return values, and the around shadows primaries, it follows that the return value of a (send) will be the around return value. If there is no around, then the return value will be that of the highest precedence primary. As mentioned before, there must always have at least one applicable primary handler.

The following table summarizes the return value of the handler types.

Handler Type Return Value

around Ignore or capture return value of next most specific around or primary
before Ignore. Side-effect only
primary Ignore or capture return value of more general primary
after Ignore. Side-effect only.

Message-handler Return Values

Get the Point

Up to now, we've discussed inheritance using only is-a links. As you've seen, this type of inheritance relationship is good for defining classes that are more and more specialized. That is, you start off by defining the most general classes as a subclass of USER, and then define more specialized classes with more slots in the lower levels of the class hierarchy.

Normally, you design new classes as specializations of existing ones. This paradigm is Inheritance by Specialization. As you recall from the quadrilateral example of Fig. 1.8 of chapter 1, the highest level is quadrilateral, and the lower levels are trapezoid, parallelogram, rectangle, and then square along one inheritance path. Trapezoid is a special class of quadrilateral, parallelogram is a special class of trapezoid, rectangle is a special class of parallelogram, and square is a special class of rectangle.

Inheritance can also be used to build up more complex classes. However, this is not quite as direct in CLIPS. As an example, the basic class for geometry is a POINT containing a single slot point1. A LINE can be then defined by adding point2 to POINT. A TRIANGLE is defined by adding point3 to LINE, and so on for QUADRILATERALS, PENTAGONS, etc.

(defclass POINT (is-a USER)

(multislot point1))

(defclass LINE (is-a POINT)

(multislot point2))

(defclass TRIANGLE (is-a LINE)

(multislot point3))

Notice how each class is a specialization of its parent class by inheriting the superclass points and then adding one new point.

The opposite paradigm is Inheritance by Generalization in which more general classes are built up from simple ones. For example, a LINE is considered made up of two points. A TRIANGLE is made up of three lines. A QUADRILATERAL is made up of four lines, and so forth. This would be a good paradigm for building an object-oriented drawing system in which new objects could be built up out of simpler ones.

There is a subtle but important difference between this example of specialization, and generalization. In specialization, new classes are built up by adding specialized slots which are the same type as superclass slots. Thus, POINT, LINE, and TRIANGLE all have point-type slots.

In contrast, generalization builds up using new types of slots defined for each class. Class POINT has a point-type slot. LINE has two point-type slots. TRIANGLE has three line-type slots. QUADRILATERAL has four line-type slots, and so on. Generalization is good for synthesis, which means a building up. The opposite of synthesis is analysis, which means taking apart or a simplification. The model for analysis is specialization.

Fig. 10.1 illustrates one inheritance scheme for polygons in which classes are built by inheritance. In this case, the link between classes would be "is-made-of". Thus, a LINE is-made-of POINT. A POLYGON is-made-of LINE, and so forth.

 

Click here for Picture

 

Fig. 10.1 Polygon Hierarchy Showing a Few Regular Polygon Classes

Links such as "is-made-of" can be simulated in CLIPS by appropriate slot definitions even though only is-a links are supported in Version 6.0. As an example of generalization, let's build up a LINE class as a generalization of a POINT class. The POINT class will provide instances that have a position. In order to make this example realistic, we'll assume an arbitrary number of dimensions by defining the position as (multiple). Thus, a one-dimensional point will have one value in the position slot, a two-dimensional point will have two values, and so forth. The definition of the POINT class is very simple.

CLIPS> (clear)

CLIPS> (defclass POINT (is-a USER)(role concrete)

(multislot position (create-accessor read-write)

(propagation no-inherit)))

CLIPS>

The (no-inherit) facet is used to prevent a LINE from inheriting a position slot. Instead, a LINE will be defined by two points called slot point1 and slot point2. These two slots will define the line and it is extraneous to have an additional position slot by inheritance.

The definition of the LINE class is a little more complex. The reason for the added complexity is that the details of implementation are included in the (defclass) because Version 6.0 only supports is-a relationships.

(defclass LINE (is-a POINT)(role concrete)

(slot point1 (create-accessor read-write)

(default-dynamic (make-instance (gensym*) of POINT))

(propagation no-inherit))

(slot point2 (create-accessor read-write)

(default-dynamic (make-instance (gensym*) of POINT))

(propagation no-inherit))

(message-handler find-point)

(message-handler print-points)

(message-handler find-distance)

(message-handler print-distance))

Note that the message-handlers of LINE are forward-declared for documentation purposes.

At this time you may be wondering why POINT and LINE are not both defined as subclasses of USER since all their slots have (no- inherit) facets. Since all the slots of POINT, LINE, and the TRIANGLE class to be defined later have (no-inherit) facets, all these classes could be defined as direct subclasses of USER rather than defining LINE as a subclass of POINT and TRIANGLE as a subclass of LINE.

However, the whole point of this example is to illustrate Inheritance by Generalization, which is a logical concept that is not directly supported by Version 6.0. Thus, defining LINE as a subclass of POINT and TRIANGLE as a subclass of LINE is done for reasons of documenting the logical concept of Inheritance by Generalization. Admittedly, a comment could be added by the (defclass LINE (is-a USER)) and (defclass TRIANGLE (is-a USER)) stating that we are trying to implement Inheritance by Generalization, but seeing the code in place is better documentation. If Inheritance by Generalization is ever directly supported by CLIPS, these (defclass) statements will make it easy to convert.

The reason for including the (make-instance (gensym*)) in the LINE slots is to provide the inheritance from the POINT class. With the standard Inheritance by Specialization, only one position slot of LINE is possible because POINT has only one position slot. It is not possible for both slot point1 and slot point2 of LINE to inherit the position slot of POINT. The actual slot value of each LINE will be a gensym* value. Each gensym* value will be the instance name of a point instance. The point position can then be accessed through the gensym* value. Thus, the gensym* values act as pointers to different instances.

This indirect access technique of (gensym*) values is analogous to using a pointer to access a value in a procedural language. Thus, the different slots of LINE can indirectly inherit the same slots of POINT. It's convenient to use (gensym*) because we don't care what the pointer names of LINE are, any more than we care what the pointer addresses are in a procedural language.

The following examples show how the points are accessed for one-dimensional points at position 0 and 1.

CLIPS> (definstances LINE_OBJECTS

(Line1 of LINE))

CLIPS> (reset)

CLIPS>

(send (send [Line1] get-point1) put-position 0)

(0)

CLIPS>

(send (send [Line1] get-point2) put-position 1)

(1)

CLIPS> (send [Line1] print)

[Line1] of LINE

(point1 [gen1])

(point2 [gen2])

CLIPS>

(send (send [Line1] get-point1) get-position)

(0)

CLIPS>

(send (send [Line1] get-point2) get-position)

(1)

CLIPS>

Now that you understand how the indirect access works, let's define some handlers to avoid the trouble of entering the nested (send) messages, as in the last two cases. Let's define a handler called find-point to print out a specified point value, and a handler called print- points to print out the values of both LINE points as follows. The argument of find-point will be either a 1 for point1 or a 2 for point2.

CLIPS> (defmessage-handler LINE find-point (?point)

(send (send ?self (sym-cat "get-point" ?point)) get-position))

CLIPS> (defmessage-handler LINE print-points ()

(printout t "point1 " (send ?self find-point 1) crlf

"point2 " (send ?self find-point 2) crlf))

CLIPS> (send [Line1] find-point 1)

(0)

CLIPS> (send [Line1] find-point 2)

(1)

CLIPS>

For real use, it would be best to provide error detection so that only a 1 or 2 is allowed.

As you can see, the handler works fine for one-dimensional points. It can be tested for two-dimensional points as follows. We'll assume the first number for each point is the X- value, and the second number is the Y- value. That is, point1 has X- value 1 and Y- value 2.

CLIPS> (send (send [Line1] get-point1) put-position 1 2)

(1 2)

CLIPS> (send (send [Line1] get-point2) put-position 4 6)

(4 6)

CLIPS> (send [Line1] print)

[Line1] of LINE

(point1 [gen1])

(point2 [gen2])

CLIPS> (send (send [Line1] get-point1) get-position)

(1 2)

CLIPS> (send (send [Line1] get-point2) get-position)

(4 6)

CLIPS>

As expected, the handler also works correctly for two-dimensional points.

Now that we have the two point positions, it's easy to find the distance between the points, which is the length of the line. The distance can be determined by defining a new handler called find-distance which uses the Pythagorean Theorem to calculate the distance as the square root of the sum of the squares. Since no assumptions were made as to the number of dimensions, the (nth) function is used to pick out each multifield value up the the maximum number of coordinates, as stored in the ?len variable.

CLIPS> (defmessage-handler LINE find-distance ()

(bind ?sum 0)

(bind ?index 1)

(bind ?len (length (send ?self find-point 1)))

(bind ?Point1 (send ?self find-point 1))

(bind ?Point2 (send ?self find-point 2))

(while (<= ?index ?len)

(bind ?dif (- (nth ?index ?Point1)

(nth ?index ?Point2)))

(bind ?sum (+ ?sum (* ?dif ?dif)))

(bind ?index (+ ?index 1)))

(bind ?distance (sqrt ?sum)))

CLIPS> (defmessage-handler LINE print-distance ()

(printout t "Distance = " (send ?self find-distance) crlf))

CLIPS> (send [Line1] print-distance)

Distance = 5.0

CLIPS>

The values 1, 2 for point1 and 4, 6 for point2 were chosen for an easy check of the handler since these coordinates define a 3-4-5 triangle. As you can see, the distance is 5.0, as expected.

Treasure Maps

Now that the POINT and LINE classes have been defined by generalized inheritance, why stop now? Let's continue with the next simplest class that can be defined from a line -- the triangle. Shown following are the three defclasses required.

(clear)

(defclass POINT (is-a USER)(role concrete)

(multislot position (create-accessor read-write)

(propagation no-inherit)))

(defclass LINE (is-a POINT)

(slot point1 (create-accessor read-write)

(default-dynamic (make-instance (gensym*) of POINT))

(propagation no-inherit))

(slot point2 (create-accessor read-write)

(default-dynamic (make-instance (gensym*) of POINT))

(propagation no-inherit)))

(defclass TRIANGLE (is-a LINE)

(slot line1 (create-accessor read-write)

(default-dynamic (make-instance (gensym*) of LINE))

(propagation no-inherit))

(slot line2 (create-accessor read-write)

(default-dynamic (make-instance (gensym*) of LINE))

(propagation no-inherit))

(slot line3 (create-accessor read-write)

(default-dynamic (make-instance (gensym*) of LINE))

(propagation no-inherit)))

Notice that the (no-inherit) facets in TRIANGLE are techically not necessary since there is no subclass of TRIANGLE defined. The reason for including the (no-inherit) facets is because of defensive-programming, which is analogous to defensive- driving. If another subclass is added, either by you or someone else, the (defclass) of TRIANGLE must be modified to include the (no-inherit) facets. This is bad style because it means that existing, debugged code must be modified. If you're going to enhance existing, debugged code, you shouldn't have to modify it. It's better to plan ahead for enhancements.

Next we'll define a triangle instance and check the instances generated. Note that your gen values may be different from those shown unless you've just started or restarted CLIPS, or have not used (gensym*) or (gensym) since you started.

CLIPS> (definstances TRIANGLE_OBJECTS

(Triangle1 of TRIANGLE))

CLIPS> (reset)

CLIPS> (instances)

[initial-object] of INITIAL-OBJECT

[Triangle1] of TRIANGLE

[gen3] of LINE

[gen4] of POINT

[gen5] of POINT

[gen6] of LINE

[gen7] of POINT

[gen8] of POINT

[gen9] of LINE

[gen10] of POINT

[gen11] of POINT

For a total of 11 instances.

CLIPS>

At first you may be surprised at all the gensym* values created. However, all of them are necessary. First, gen3 was created for slot line1, which required gen4 and gen5 for the slots point1 and point2 associated with it by inheritance. Second, gen6 was created for slot line2, which required gen7 and gen8 for its slots point1 and point2. Finally, gen9 was created for slot line3, which required gen10 and gen11 for the slots point1 and point2 associated with it . The slots for [Triangle1] and one of its pointer values, [gen3], is shown following.

CLIPS> (send [Triangle1] print)

[Triangle1] of TRIANGLE

(line1 [gen3])

(line2 [gen6])

(line3 [gen9])

CLIPS> (send [gen3] print)

[gen3] of LINE

(point1 [gen4])

(point2 [gen5])

CLIPS>

Now lets put in the X, Y coordinates of [Triangle1] as follows.

(send (send (send [Triangle1] get-line1) get-point1) put-position -1 0)

(send (send (send [Triangle1] get-line1) get-point2) put-position 0 2)

(send (send (send [Triangle1] get-line2) get-point1) put-position 0 2)

(send (send (send [Triangle1] get-line2) get-point2) put-position 1 0)

(send (send (send [Triangle1] get-line3) get-point1) put-position 1 0)

(send (send (send [Triangle1] get-line3) get-point2) put-position -1 0)

The stored values are as follows.

CLIPS> (send [Triangle1] print)

[Triangle1] of TRIANGLE

(line1 [gen3])

(line2 [gen6])

(line3 [gen9])

CLIPS> (send [gen3] print)

[gen3] of LINE

(point1 [gen4])

(point2 [gen5])

CLIPS> (send [gen4] print)

[gen4] of POINT

(position -1 0)

CLIPS> (send [gen5] print)

[gen5] of POINT

(position 0 2)

CLIPS>

As you can see, the line1 pointer [gen1] points to point1 and point2 with their pointers [gen2] and [gen3]. These last two pointers finally point to the actual values of (-1 0) and (0 2) that define line1 of [Triangle1]. It's analogous to Long John Silver finding a treasure chest with a map, [gen1], which leads to another chest with two maps, [gen2] and [gen3], which lead to the two buried treasures at the locations specified by [gen2] and [gen3].

The values stored for each line of [Triangle1] can be retrieved by a single command using nested messages such as the following.

(send (send (send [Triangle1] get-line1)

get-point1)

get-position)

Although these commands work, it's not much fun to type them in unless you get paid by the hour and need the typing practice. As you might have guessed from the LINE handlers that we defined in the previous section, it's possible to define TRIANGLE handlers as follows.

(defmessage-handler TRIANGLE find-line-point (?line ?point)

(send (send (send ?self (sym-cat "get-line" ?line))

(sym-cat "get-point" ?point)) get-position))

(defmessage-handler TRIANGLE print-line (?line)

(printout t "point1 " (send ?self find-line-point ?line 1) crlf

"point2 " (send ?self find-line-point ?line 2) crlf))

CLIPS> (send [Triangle1] print-line 1)

point1 (-1 0)

point2 (0 2)

CLIPS>

Using these handlers is a lot more convenient than typing in the nested messages.

At this point, you might be tempted to define a handler called find-line which returns both point values of the specified line. Recall that find-line-point requires the specification of both the line and one of the two points which define the line. So why not just send two messages in the same handler to return both point values of the specified line? Shown following is the handler for find-line and what it returns for line1 of [Triangle1].

(defmessage-handler TRIANGLE find-line (?line)

(send (send (send ?self (sym-cat "get-line" ?line)) get-point1) get-position)

(send (send (send ?self (sym-cat "get-line" ?line)) get-point2) get-position))

CLIPS> (send [Triangle1] find-line 1)

(0 2)

CLIPS>

As you can see, the handler only returns the last message value of (0 2). Thus, the first value of (-1 0) is not returned by CLIPS. This is like the case of deffunctions which only return the last action. One way of getting around this problem and returning both point values of the line is shown following.

(defmessage-handler TRIANGLE find-line (?line)

(create$ (send (send (send ?self (sym-cat "get-line" ?line)) get-point1) get-position)

(send (send (send ?self (sym-cat "get-line" ?line)) get-point2) get-position)))

CLIPS> (send [Triangle1] find-line 1)

(-1 0 0 2)

CLIPS>

Notice that the (create$) function was used to combine both point values into a single multifield value (-1 0 0 2) which was then returned.

Other Features

A number of other functions are useful with handlers. Some of these follow.

Function Meaning

undefmessage-handler Deletes a specified handler

listdefmessage-handlers Lists the handlers

delete-instance Operates on the active instance

message-handler-existp Returns TRUE if handler exists, else FALSE

The grouping functions group COOL items into a multifield variable.

Function Meaning

get-defmessage-handler-list Groups the class names, message names and types (direct or inherited)

class-superclasses Groups all superclass names (direct or inherited.)

class-subclasses Groups all subclass names (direct or inherited).

class-slots Groups all slot names (explicitly defined or inherited)

slot-existp Returns TRUE if class slot exists, else FALSE

slot-facets Groups the specified slot facet values of a class

slot-sources Groups the slot names of classes which contribute to a slot in the specified class

The preview-send function is useful in debugging since it displays the sequence of all handlers that potentially may be involved in processing a message. The reason for the term potentially is that shadowed handlers will not be executed if the shadower does not use call- next- handler or override- next- handler.

Handlers are arranged in a messagehandler precedence which determines how they are called. The process of determining which handlers should be called and in what order is called the message dispatch. Every time a message is sent to an object, CLIPS arranges the message dispatch for the applicable handlers of that object, which can be viewed by the (preview-send) command. The applicable handlers are all handlers in all classes along the object's inheritance path that may respond to the type of message. Other functions useful with pattern matching objects by rules follow.

Function Meaning

object-pattern-match-delay Delay pattern matching of rules until after instances are created, modified, or deleted

modify-instance Modifies instance using slot overrides. Object pattern matching delayed until after modifications.

active-modify-instance Change the values of the instance concurrent with object pattern matching with direct- modify message

message-modify-instance Change the values of the instance. Delay object pattern matching until all slots are changed

active-message-modify-instance Change the values of the instance concurrent with object pattern matching using message- modify

Chapter 12 Questions and Answers

The best way to learn is by asking yourself questions; the best way to be sorry is by answering all of them.

In this chapter you'll learn how to pattern match on instances. One way is with rules. Also, CLIPS has a number of query functions to match instances. In addition, control facts and slot daemons can be used for pattern matching.

Object Lessons

One of the new features of Version 6.0 is the ability of rules to pattern match on objects. In order to use this feature you must first specify whether a class is reactive to pattern matching on the LHS of rules using the pattern-match role. If the pattern-match is reactive, the class may be pattern matched. If the class is nonreactive, it is not. The default is non-reactive.

You can also specify whether a slot facet reactive or non-reactive using the slot facet pattern-match reactive or pattern-match non-reactive. The following example shows how the value of the slot sound is pattern matched by a rule.

CLIPS> (clear)

CLIPS>

(defclass DUCK (is-a USER)(role concrete)(pattern-match reactive)

(multislot sound (create-accessor read-write)

(default quack quack)))

CLIPS> (make-instance [Dorky_Duck] of DUCK)

[Dorky_Duck]

CLIPS> (make-instance [Dinky_Duck] of DUCK)

[Dinky_Duck]

CLIPS> (defrule find-sound

?duck <- (object (is-a DUCK)(sound $?find))

=>

(printout t "Duck " (instance-name ?duck) " says " ?find crlf))

CLIPS> (run)

Duck [Dinky_Duck] says (quack quack)

Duck [Dorky_Duck] says (quack quack)

CLIPS>

The object-pattern conditional element object is followed by the classes and slots to be matched against. Following the is-a and the slot-name can be constraint expressions involving ?, $?, &, and |.

In addition, instance names can be specified for pattern matching. The following example shows how only one instance of the DUCK class is matched using the name constraint, name, of instances. Note that name is a reserved word and cannot be used as a slot name.

CLIPS> (defrule find-sound

?duck <- (object (is-a DUCK)(sound $?find)(name [Dorky_Duck]))

=>

(printout t "Duck " (instance-name ?duck) " says " ?find crlf))

CLIPS> (run)

Duck [Dorky_Duck] says (quack quack)

CLIPS>

Objects in the Database

Consider the following general type of problem. Given some instances, how many satisfy a specified condition? For example, shown following are the defclasses and definstances of Joe's Home showing the various types of sensors and the appliances connected to them. Notice that an abstract class DEVICE is defined since both SENSOR and APPLIANCE inherit common slots type and location.

(clear)

(defclass DEVICE (is-a USER)(role abstract)

(slot type (create-accessor read-write)(access initialize-only));Sensor type

(slot loc (create-accessor read-write)(access initialize-only)));Location

(defclass SENSOR (is-a DEVICE)(role concrete)

(slot reading (create-accessor read-write))

(slot min (create-accessor read-write)(access initialize-only)) ;Min reading

(slot max (create-accessor read-write)(access initialize-only)) ;Max reading

(slot app (create-accessor read-write)(access initialize-only)));SEN. APP.

(defclass APPLIANCE (is-a DEVICE)(role concrete)

(slot setting (create-accessor read-write)) ; Depends on appliance

(slot status (create-accessor read-write))) ; off or on

(definstances ENVIRONMENT_OBJECTS

(T1 of SENSOR (type temperature)

(loc kitchen)

(reading 110) ; Too hot

(min 20)

(max 100)

(app FR))

(T2 of SENSOR (type temperature)

(loc bedroom)

(reading 10) ; Too cold

(min 20)

(max 100)

(app FR))

(S1 of SENSOR (type smoke)

(loc bedroom)

(reading nil) ; Bad sensor nil reading

(min 1000)

(max 5000)

(app SA))

(W1 of SENSOR (type water)

(loc basement)

(reading 0) ; OK

(min 0)

(max 0)

(app WP))

(FR of APPLIANCE (type furnace)

(loc basement)

(setting low) ; low or high

(status on))

(WP of APPLIANCE (type water_pump)

(loc basement)

(setting fixed)

(status off))

(SA of APPLIANCE (type smoke_alarm)

(loc basement)

(setting fixed)

(status off)))

Suppose the following questions or queries are asked. What are all the objects in the database? How are all the objects arranged? What are the relationships between objects? What are all the devices? What are all the sensors? What are all the appliances? Which sensor is connected to which appliance? Are there any sensors whose type is temperature? What sensors of type temperature have a reading between min and the max? An even more basic query is whether or not there are any sensors present.

The query system of COOL is a set of six functions that may be used for pattern matching an instance-set and performing actions. An instance-set is a set of instances, such as the instances of SENSOR. The instances in the instance-set may come from multiple classes that do not have to be related. In other words, the classes do not have to be from the same inheritance path.

The following table from the CLIPS Reference Manual, summarizes the predefined query functions that may be used for instance-set access.

Instance-set Query Functions

I'll Take Any

The any-instancep function is a predicate function that returns TRUE if there is an instance matching the pattern and FALSE otherwise. Shown following is an example of this query function used with the SENSOR and APPLIANCE classes and instances. The query function determines if there is any instance in the SENSOR class.

CLIPS> (reset)

CLIPS> (instances)

[initial-object] of INITIAL-OBJECT

[T1] of SENSOR

[T2] of SENSOR

[S1] of SENSOR

[W1] of SENSOR

[FR] of APPLIANCE

[WP] of APPLIANCE

[SA] of APPLIANCE

For a total of 8 instances.

CLIPS> (any-instancep ((?ins SENSOR)) TRUE)

TRUE ;Function returns TRUE because there is a SENSOR instance

CLIPS> (any-instancep ((?ins DUCK)) TRUE) ; Evaluation error--Bad!

[PRNTUTIL1] Unable to find class DUCK. ; No DUCK class

CLIPS>

The basic format of a query function involves an instance-set-template to specifies the instances and their classes, an instance-set-query as the boolean condition that the instances must satisfy, and an action to specifies the single action to be taken. Multiple actions can be included by grouping them with the progn function.The predicate function class-existp returns TRUE if the class exists and FALSE otherwise.

The combination of instance name followed by the one or more class restrictions is called an instancesetmembertemplate. The query functions may generally be used like any other function in CLIPS. Shown following are the Rules of Scope which describe the restrictions on the use of variables in a query function. The term scope means the section of code where a variable is visible or known. The term reference means the name or address by which a variable is accessed. In other words, the scope of a variable means where the variable can be referenced, e.g., bound or printed. Anything which is not prohibited by these rules is allowed, such as nesting. Also, the term query refers to the query portion of the query function, not the query function itself.

There are two steps involved in trying to satisfy a query. First, CLIPS generates all the possible instance-sets that match the instance-set-template. Second, the boolean instance-set-query is applied to all the instance-sets to see which ones, if any, satisfy the query. Instance-sets are generated by a simple permutation of the members in a template, where the rightmost members are varied first. Note that a permutation is not the same as a combination because order matters in a permutation but not in a combination.

The function find-all-instances returns a multifield value of all instances which satisfy the query, or an empty multifield value for none. The do-for-instance query function is similar to find-instance except that it performs a single distributed action when the query is satisfied. The do-for-all-instances function is similar to the do-for-instance except that it performs an action for every instance-set that satisfies the query.

Design Decisions

In contrast to rules which are only activated when their patterns are satisfied, deffunctions are explicitly called and then executed. Just because a rule is activated does not mean it will be executed. Deffunctions are completely procedural in nature because once called by name, their code is executed in a procedural manner, statement by statement. Also, no pattern matching involving constraints is used in a deffunction to decide if its actions should be executed. Instead, any arguments that match the number expected by the deffunction argument list will satisfy the deffunction and cause its actions to be executed.

The basic idea of deffunctions as named procedural code is carried to a much greater degree with defgenerics and the defmethods that describe their implementation. A defgeneric is like a deffunction but much more powerful because it can do different tasks depending on its argument constraints and types. The ability of a generic function to perform different actions depending on the classes of its arguments is called overloading the function name.

By proper use of operator overloading, it's possible to write code that is more readable and reusable. For example, a defgeneric for the "+" function can be defined with different defmethods. The expression,

(+ ?a ?b)

could add two real numbers represented by ?a and ?b, or two complex numbers, or two matrices, or concatenate two strings, and so forth depending if there is a defmethod defined for the argument classes. CLIPS does this by first recognizing the type of the arguments and then calling the appropriate defmethod defined for those types. A separate overloaded defmethod for "+" would be defined for each set of argument types except for the predefined system types such as real numbers. Once the defgeneric is defined, it's easy to reuse in other programs.

Any named function that is system defined or external can be overloaded using a generic function. Notice that a deffunction cannot be overloaded. An appropriate use of a generic function is to overload a named function. If overloading is not required, you should define a deffunction or an external function.

The syntax of defgenerics is very simple, consisting of just the legal CLIPS symbol name and an optional comment.

(defgeneric <name> [<comment>])

As a simple example of generic functions, consider the following attempt in CLIPS to compare two strings using the ">" function.

CLIPS> (clear)

CLIPS> (> "duck2" "duck1")

[ARGACCES5] Function > expected argument #1 to be of type integer or float

CLIPS>

It's not possible to do this comparison with the ">" function because it expects NUMBER types as arguments.

However, it's easy to define a (defgeneric) which will overload the ">" to accept STRING types as well as NUMBER types. For example, if the arguments of ">" are of type STRING, the defgeneric will do a string comparison, letter by letter starting from the left until the ASCII codes differ. In contrast, if the arguments of ">" are of type NUMBER, the system compares the sign and magnitude of the numbers. The user- defined ">" for STRING types is an explicit method, while a system-defined or user-defined external function such as ">" for NUMBER type is an implicit method.

The technique of overloading a function name so that the method which implements it is not known until run-time is another example of dynamic binding. Any object reference of name or address may be bound at run-time in CLIPS to functions through dynamic binding also.

Some languages such as Ada have a more restrictive type of overloading in which the function name must be known at compile time rather than at run-time. The run-time dynamic binding is the least restrictive since methods can be created during execution by the (build) statement. However, you should be careful in using (build) since dynamically creating constructs is often hard to debug. Also, the resulting code may be difficult to verify and validate since you'll have to stop execution to examine the code. Dynamic binding is a characteristics of a true object- oriented programming language.

Following is an example of a defgeneric, ">", for STRING types and its method.

CLIPS> (defgeneric >) ; Header declaraction. Actually unnecessary

CLIPS> (defmethod > ((?a STRING) (?b STRING))

(> (str-compare ?a ?b) 0))

CLIPS> (> "duck2" "duck1") ; The overload ">" works correctly

TRUE ; in all three cases.

CLIPS> (> "duck1" "duck1")

FALSE

CLIPS> (> "duck1" "duck2")

FALSE

CLIPS>

The (defgeneric) acts as a header declaration to declare the type of function being overloaded. It's not actually necessary to use a defgeneric in this case because CLIPS implicitly deduces the function name from the defmethod name, which is the first symbol following "defmethod". The header is a forward declaration that is necessary if the (defgeneric) methods have not yet been defined, but other code such as defrules, defmessage-handlers, and so forth refers to the (defgeneric) name.

Other Features

Compared to deffunctions, a method has an optional method index. If you don't supply this index, CLIPS will provide a unique index number among the methods for that generic function, that can be viewed by the listdefmethods command. The method body can be printed using the ppdefmethod command. A method can be removed with an undefmethod function call.

The ranking of methods determines the method precedence of a generic function. It is the method precedence which determines the methods order of listing. Higher precedence methods are listed before lower precedence methods. The highest precedence method will also be tried first by CLIPS.

A shadowed method is one in which one method must be called by another. The process by which CLIPS picks the method with highest precedence is called the generic dispatch. For more information, see the CLIPS Reference Manual.

CLIPS Main Features

A Tool for the Development and Delivery of Expert Systems

CLIPS is a productive development and delivery expert system tool which provides a complete environment for the construction of rule and/or object based expert systems. CLIPS is being used by over 4,000 users throughout the public and private community including: all NASA sites and branches of the military, numerous federal bureaus, government contractors, universities, and many companies. The key features of CLIPS are:

  • Knowledge Representation: CLIPS provides a cohesive tool for handling a wide variety of knowledge with support for three different programming paradigms: rule- based, object- oriented and procedural. Rule- based programming allows knowledge to be represented as heuristics, or "rules of thumb," which specify a set of actions to be performed for a given situation. Object-oriented programming allows complex systems to be modeled as modular components (which can be easily reused to model other systems or to create new components). The procedural programming capabilities provided by CLIPS are similar to capabilities found in languages such as C, Pascal, Ada, and LISP.
  • Portability: CLIPS is written in C for portability and speed and has been installed on many different computers without code changes. Computers on which CLIPS has been tested include IBM PC compatibles, Macintosh, VAX 11/780, and Sun 3/260. CLIPS can be ported to any system which has an ANSI compliant C compiler. CLIPS comes with all source code which can be modified or tailored to meet a user's specific needs.
  • Integration/Extensibility: CLIPS can be embedded within procedural code, called as a subroutine, and integrated with languages such as C, FORTRAN and ADA. CLIPS can be easily extended by a user through the use of several well-defined protocols.
  • Interactive Development: The standard version of CLIPS provides an interactive, text oriented development environment, including debugging aids, on-line help, and an integrated editor. Interfaces providing features such as pulldown menus, integrated editors, and multiple windows have been developed for the Macintosh, Windows 3.1, and X Window environments.
  • Verification/Validation: CLIPS includes a number of features to support the verification and validation of expert systems including support for modular design and partitioning of a knowledge base, static and dynamic constraint checking of slot values and function arguments, and semantic analysis of rule patterns to determine if inconsistencies could prevent a rule from firing or generate an error.
  • Fully Documented: CLIPS comes with extensive documentation including a Reference Manual and a User's Guide.
  • ADA Version: A version of CLIPS developed entirely in Ada and containing a subset of the features found in the C version of CLIPS is currently available for VAX and UNIX workstations.
  • Availability: CLIPS version 6.0 and CLIPS/Ada version 4.4 are currently available. CLIPS is free to NASA, USAF, and their contractors for use on NASA and USAF projects by calling the Software Technology Branch Help Desk between the hours of 9:00 AM to 4:00 PM (CST) Monday through Friday at (713) 286-8919. The STB Help Desk can also be reached via electronic mail at <stbprod@fdr.jsc.nasa.gov> or by FAX at (713) 286-4479. Government contractors should have their contract monitor call the Software Technology Branch Help desk to obtain CLIPS. Others may purchase CLIPS (including all documentation) from COSMIC at a nominal fee for unlimited copies with no royalties. Further information is available by calling COSMIC at (706) 542-3265. An electronic bulletin board containing information regarding CLIPS can be reached 24 hours a day at (713) 286-7252 or (713) 286-5375. Communications information is 300, 1200, or 2400 baud, no parity, 8 data bits, and 1 stop bit.

Bibliography of CLIPS Publications

G. Riley, "Benchmarking Expert System Tools," Proceedings of ROBEX '86, NASA/Johnson Space Center, Houston, TX, June 1986.

G. Riley, "Implementation of an Expert System Shell on a Parallel Computer," Proceedings of The Third Annual Artificial Intelligence & Advanced Computer Technology Conference, Long Beach Convention Center, Long Beach, CA, April 1987.

G. Riley, "Implementing CLIPS on a Parallel Computer," Proceedings of The First Annual Workshop on Space Operations Automation and Robotics (SOAR `87), NASA/Johnson Space Center, Houston, TX, August 1987.

C. Culbert, G. Riley, and R. Savely, "Approaches to the Verification of Rule-Based Expert Systems," Proceedings of The First Annual Workshop on Space Operations Automation and Robotics (SOAR `87), NASA/Johnson Space Center, Houston, TX, August 1987.

G. Riley, C. Culbert, R. Savely, and F. Lopez, "CLIPS: An Expert System Tool for Delivery and Training," Proceedings of the Third Conference on Artificial Intelligence for Space Applications, Huntsville, AL, November 1987.

C. Culbert, G. Riley, and R. Savely, "Verification Issues for Rule-Based Expert Systems," Proceedings of the Third Conference on Artificial Intelligence for Space Applications, Huntsville, AL, November 1987.

C. Culbert, G. Riley, R. Savely, and J. Giarratano, "A Solution to the Expert System Delivery Problem," Proceedings of the ISA/88, Houston, TX, October 1988.

G. Riley, C. Culbert, and R. Savely, "CLIPS: An Expert System Tool for Training, Development, and Delivery," Intelligent Systems Review, Volume 1, Number 1, Fall 1988.

Joseph C. Giarratano, Chris Culbert, and Robert T. Savely, "The State of the Art for Current and Future Expert System Tools," ISA Transactions, Vol. 29, No. 1, pp. 17-25, Jan. 1990

G. Riley and B. Donnell, "Advanced CLIPS Capabilities," Proceedings of The Fourth Annual Workshop on Space Operations Applications and Research (SOAR `90), NASA/Johnson Space Center, Albuquerque, NM, June 1990.

G. Riley, "CLIPS: A Tool for the Development and Delivery of Expert Systems," Proceedings of the Technology 2000 Conference, Washington, DC, November 1990.

G. Riley, "CLIPS: An Expert System Building Tool," Proceedings of the Technology 2001Conference, San Jose, CA, December 1991.

Joseph C. Giarratano and Gary Riley, Expert Systems Principles and Programming, PWS Pub. Co.

Proceedings of the First CLIPS Users Conference

Aug. 13-15, 1990

NASA/Johnson Space Center, Gilruth Center

NASA Conference Publication 10049

A1 SESSION: Engineering Applications

A1.1-W. J. Parkinson, G.F. Luger, R.E. Bretz

Three CLIPS-Based Expert Systems for Solving Engineering Problems

A1.2-Ken Porter

Building Engineering Expert Systems in CLIPS

B1 SESSION: Intelligent Tutors and Training

B1.1-Randall W. Hill, Jr., Brad Pickering

Intelligent Tutoring Using HyperCLIPS

B1.2-Grace Hua

Developing An Intelligent Computer-Aided Trainer

B1.3-Stephen J. Mueller

Incorporating CLIPS into a Personal-Computer-Based Intelligent Tutoring System

A2 SESSION: Intelligent Software Engineering

A2.1-Barry W. Cameron

Hardware Independence Checkout Software

A2.2-Keith Morris

Automating Symbolic Analysis with CLIPS

B2 SESSION: Automated Knowledge Acquisition I

B2.1-Dr. Vishweshwar V. Dixit

EDNA: Expert Fault Digraph Analysis Using CLIPS

B2.2 Janice A. Jordan, Min-Jin Lin, Richard J. Mayer, Mark E. Sterle

A Middle Man Approach To Knowledge Acquisition in Expert Systems

A3 SESSION: Network Applications

A3.1-Roger F. Hansen

JESNET Expert Assistant

A3.2-Albert Leigh

The Network Management Expert System Prototype for Sun Workstations

A3.3-Tom Wannemacher

Using CLIPS in A Distributed System - The Network Control Center (NCC) Expert System

B3 SESSION: Automated Knowledge Acquisition II

B3.1-Larry Mason

From Data Rich to Information Wealthy-A CASE for CLIPS

B3.2-Tim Saito

Supplemental Knowledge Acquisition through External Product Interface for CLIPS

B3.3-Gary B. Young

Rule Induction Techniques

A4 ESSION: Verification and Validation

A4.1-Ravi M. Rangan

Enforcing Compatibility and Constraint Conditions and Information Retrieval at the Design Action

A4.2-J. B. Coombs, C Chang, R. a> Stachowitz

Validation of Knowledge-based Systems

B4 SESSION: Enhancements to CLIPS-General I

B4.1-James L. Rogers

Decomposing a Complex Design Problem Using CLIPS

B4.2-Jaye Hicks

Fault-Tolerant, Embedded CLIPS Applications

B4.3-Wesley A. White

CLIPS/Ada-An Ada-Based Tool for Building Expert Systems

A5 SESSION: Space Shuttle Quality Control/Diagnosis

A5.1-Luis M. Flores, Roger F. Hansen

System Control Module Diagnostic Expert Assistant

A5.2-George D. Lardas

Prototype Automated Post-MECO Ascent I-Load Verification Data Table

A5.3-Amy Y. Murphey

An Expert System to Manage the Operation of the Space Shuttle's Cryogenic Fuel Tank Cryogenic Reactant Tanks

B5 SESSION: Enhancements to CLIPS-General II

B5.1-Mala Mehrota, Sally C. Johnson

Rule Groupings in Expert Systems

B5.2-James R. Geissman

Automatically Structuring and Translating CLIPS

A6 SESSION: Space Shuttle and Real-time Applications

A6.1-Donald Culp

Interpretation of Space Shuttle Telemetry

A6.2-Arthur N. Rasmussen

The INCO Expert System Project-CLIPS in Shuttle Mission Control

A6.3-R. J. Frainier, N. Groleau, R. Bhatnagar. C. Lam, M. Compton, S. Colombano, S. Lai, P. Szolovits, M. Manahan, I. Statler, L. Young

A Comparison of CLIPS and LISP-Based Approaches to the Development of a Real-time Expert System

A6.4-Joseph D. Mainardi, Dr. Gerry Szatkowski

Knowledge Base Rule Partitioning Design for CLIPS

A6.5-Scott A. Dudek, Matthew R. Barry

Space Shuttle Systems Monitoring: Real-Time Telemetry Processing Using CLIPS

B6 SESSION: Medical, Biological and Agricultural Applications

B6.1-Sarjeev Batra, Bradley University

GENEX: A Knowledge-based Expert Assistant for Genbank Data Analysis

B6.2-Robert H. Fritz

Knowledge Assisted Diagnosis of Mood Disorders Using DSM-III

B6.3-Dr. Gary C. Salzman

A CLIPS Expert System for Clinical Flow Cytometry Data Analysis

B6.4-Dr. Bernard A. Engel, D.D. Jones, R.L. Rhykerd, L.M. Rhykerd, C.L. Rhykerd, Jr.

A CLIPS Expert System for Maximizing Alfalfa (Medicago Sativa L.) Production

B6.5-Dr. Chi N. Thai, J.N. Pease, R.L. Shewfelt

A Decision Support System for Delivering Optimal Quality Peach and Tomato

A7 SESSION: Quality Control Applications

A7.1-Cpt. John F. Mack

The Table of Distribution and Allowances (TDA) System Analyzer

A7.2-Richard O'Donnell

MOM-A Meteorological Data Checking Expert System in CLIPS

A7.3-Mark Tischendorf

Automated Decision Stations

B7 SESSION: Intelligent Databases, and Networks

B7.1-Lynn Fischer, Judson D. Cary

ISLE: Intelligent Selection of Loop Electronics-A CLIPS/C++/INGRES Integrated Application

B7.2-James Snyder, Dr. Laurian Chirica

An SQL Query Generator for CLIPS

B7.3-Bernard P. Wess

_CLIPSE = Presentation Management + NASA CLIPS + SQL

A8 SESSION: Space Station Freedom Applications

A8.1-Christopher Marsh

A PC Based Fault Diagnosis Expert System

B8 SESSION: User Interface I

B8.1-Dr. Bernard A. Engel, C.C. Rewerts, R. Srinivasan, J.B. Rogers, Dr. D.D. Jones

CLIPS Interface Development Tools and Their Application

B8.2-Charles R. Patton

CLIPS-A Proposal for Improved Usability

B8.3-Brad Pickering, Randall W. Hill, Jr.

HyperCLIPS-A HyperCard Interface to CLIPS

A9 SESSION: Space Shuttle and Satellite Applications

A9.1-Thomas P. Gathmann

A Dynamic Satellite Simulation Testbed Based on CLIPS and CLIPS-Derived Tools

A9.2-Dr. Christopher Landauer

Analysis of MMU FDIR Expert System

A9.3-Barbara Pauls

Satellite Simulations Utilizing CLIPS

B9 SESSION: User Interface II

B9.1-Dr. Thomas J. Nagy

Improving the Human Factors of Software with CLIPS

B9.2-Mark Sterle, Richard J. Mayer, Janice A. Jordan, Howard N. Brodale, Min-Jin Lin

A Memory Efficient User Interface for CLIPS Micro-computer Applications

B9.3-Ross C. Miller, Chuck Kosta, Matt Vesty

Prototyping User Displays Using CLIPS

A10 SESSION: Artificial Neural Systems and Fuzzy Logic

A10.1-Elizabeth Charnock, Norman Eng

CLIPS on the NeXT Computer

A10.2-Dr. Cathy H. Wu, Pamela A. Taylor, George M. Whitson, Cathy Smith

CLIPS-A Tool for Corn Disease Diagnostic System and an Aid to Neural Network for Automated Knowledge Acquisition

A10.3-Brenda McGee, Himanshu Bhatnagar

A Neural Network Simulation Package in CLIPS

B10 SESSION: Enhancements to CLIPS: Reasoning/Representation

B10.1-Hisham Assal, Dr. Leonard Myers

Implementation of a Frame-Based Representation in CLIPS

B10.2-Aurora C. Diaz, Robert A. Orchard

BB_CLIPS-Blackboard Extensions to CLIPS

A11 SESSION: Parallel and Distributed Processing I

A11.1-Steve Geyer

CLIPS Meets the Connection Machine or How to Create a Parallel Production System

A11.2-David Goldstein

PRAIS-Distributed, Real-time Knowledge-Based Systems Made Easy

B11 SESSION: Enhancements to CLIPS-Object Oriented

B11.1-Mark Auburn

Integrating an Object System into CLIPS-Language Design and Implementation Issues

B11.2-M. Aldrobi, S. Anastasiadis, B. Khalife, M. Galler, K. Kontogiannis, Prof. Renato De Mori

CLIPS Enhanced with Objects, Backward Chaining, and Explanation Facilities

B11.3-David S. Logie, H. Kamil

Integration of Object-Oriented Knowledge Representation with the CLIPS Rule-Based System

B11.4-Clifford Sobkowicz

An Object-Oriented Extension to CLIPS

A12 SESSION: Parallel and Distributed Processing II

A12.1-Dr. Leonard Myers, Coe Johnson, Dean Johnson

MARBLE - A System for Executing Expert Systems in Parallel

A12.2-Dr. Roger Schultz, Iain Stobie

Building Distributed Rule-Based Systems Using the AI Bus

A12.3-James Taylor, Dr. Leonard Myers

Executing CLIPS Expert Systems in a Distributed Environment

B12 SESSION: Enhancements to CLIPS:Graphics/X-Windows

B12.1-Andres C. Callegari

Integrating Commercial off-the-shelf (COTS) Graphics and Extended Memory Packages with CLIPS

B12.2-Ben M. Faul

Constructing Complex Graphics Applications with CLIPS and the X-Window System

b13.3-Dr. Terry Feagin

A Graphical Interface to CLIPS Using SunView

A13 SESSION: Aerospace Applications

A13.1-Matthew R. Barry

On a Production System Using Default Reasoning for Pattern Classification

A13.2-Tim Conway

Embedding CLIPS in a Data-base-Oriented Diagnostic System

A13.3-Dr. Pamela K. Fink, David T. Lincoln

UFC Advisor-An AI-Based System for the Automatic Test Environment

B13 SESSION: Advisory Systems I

B13.1-Chet Lund

Expert System for Scheduling Simulation Lab Sessions

B13.2-Dave Lavery, William D. Brooks

MacDoctor-The Macintosh Diagnoser

B13.3-S. Al-Mutawa, V. Srinivas, Dr. Young B. Moon

Development of an Instructional Expert System for Hole Drilling Processes

A14 SESSION: Simulation and Defense

A14.1-Dr. Linfu Cheng, John D. McKendrick, Jeff Liu, Elcee Computek, Inc.

Knowledge/Geometry-Based Mobile Autonomous Robot Simulator KMARS

A14.2-Brett Gossage

Embedded CLIPS for SDI BM/C3 Simulation and Analysis

A14.3-Patrick McConagha, Joseph Reynolds

Embedding CLIPS-Based Expert Systems in a Real-time Object-Oriented Simulation

B14 SESSION: Advisory Systems and Tutors

B14.1-Dr. David R. Read

SPILC-An Expert Student Advisor

B14.2-David J. Swanson

Prediction of Shipboard Electromagnetic Interference (EMI) Problems Using Artificial Intelligence (AI) Technology

B14.3-Andrew Warinner

Building an Intelligent Tutoring System for Procedural Domains

B14.4-Dr. Patrick Krolak, Mark Miller, Brenda McGee, Stanley J. Barr

Integrating PCLIPS into ULowell's Lincoln Logs Factory of the Future

A15 SESSION: Intelligent Control

A15.1-Cody R. Nivins

A Object-Oriented Generic Controller Using CLIPS

A15.2-A.A. Rabeau, K.D. Jamison, A. Bensaoula, C. Horton, A. Ignatiev, J.G. Glover

Applying CLIPS to Control of Molecular Beam Epitaxy Processing

Proceedings of the Second CLIPS Users Conference

Sept. 23-25, 1991

NASA/Johnson Space Center, Gilruth Center

NASA Conference Publication 10085

Volume 1

Page

AGENDA 3

SESSION 1

Rule Groupings: An Approach Towards Verification of Expert Systems 21

Enhanced Use of CLIPS at the Los Alamos National Laboratory 25

SESSION 2A.

Using a CLIPS Expert System to Automatically Manage TCP/IP

Networks and Their Components 41

NMESys: An Expert System for Network Fault Detection 52

A Mission Executor for an Autonomous Underwater Vehicle 58

SESSION 2B

The Automated Army ROTC Questionnaire (ARQ) 71

Decision Blocks: A Tool for Automating Decision Making in CLIPS 76

Automated Predictive Diagnosis (APD): A Three Tiered

Shell for Building Expert Systems for Automated Prediction and Decision Making 89

ICADS: A Cooperative Decision Making Model With CLIPS Experts 102

SESSION 3A

A CLlPS/-Window Interface 151

Application of Machine Learning and Expert Systems to

Statistical Process Control (SPC) Chart Interpretation 123

Application of Software Technology to Automatic Test Data Analysis 139

SESSION 3B

Acquisition, Representation and Rule Generation for Procedural Knowledge 149

Projects in an Expert System Class 162

Using CLIPS as the Cornerstone of a Graduate Expert Systems Course 166

SESSION 4A

CRN5EXP - Expert System for Statistical Quality Control 173

Distributed Semantic Networks and CLIPS 177

Object-Oriented Knowledge Representation for Expert Systems 186

SESSION 4B

Linkfinder: An Expert System that Constructs Phylogenic Trees 199

Generating Target System Specifications from a Domain Model Using CLIPS 209

The Management and Security Expert (MASE) 227

Volume 2

SESSION 5A

Adding Run History to CLIPS 237

CLIPS Application User Interface for the PC 253

Expert Networks in CLIPS 267

ECLIPS: An Extended CLIPS for Backward Chaining and Goal-Directed Reasoning 273

SESSION 5B

Extensions to the Parallel Real-Time Artificial Intelligence

System (PRAIS) for Fault-Tolerant Heterogeneous Cycle-Stealing Reasoning 287

PCLIPS- Parallel CLIPS 294

Separating Domain and Control Knowledge Using Agenda 307

Integrating CLIPS Applications into Heterogeneous Distributed Systems 308

SESSION 6A

Data-Driven Backward Chaining 325

Automated Information Retrieval Using CLIPS 332

Proposal for a CLIPS Software Library 344

SESSION 6B

Improving NAVFAC's Total Quality Management of

Construction Drawings with CLIPS 357

Validation of an Expert System Intended for Research in

Distributed Artificial Intelligence 365

Testing Validation Tools on CLlPS-Based Expert Systems 382

SESSION 7A

Design Concepts for Integrating the IMKA Technology with CLIPS 395

A CLlPS-Based Tool for Aircraft Pilot-Vehicle Interface Design 407

On the Generation of Graphical Objects and Images from within CLIPS Using XView 417

SESSION 7B

Passive Acquisition of CLIPS Rules 423

YUCSA: A CLIPS Expert Database System to Monitor Academic Performance 436

A CLIPS Based Personal Computer Hardware Diagnostic System 445

SESSION 8A

PVEX - An Expert System for ProducibilityNalue

Engineering 455

Rule Groupings in Expert Systems Using Nearest Neighbour

Decision Rules and Convex Hulls 464

Debugging Expert Systems Using a Dynamically Created Hypertext Network 475

SESSION 8B

Implementing a Frame Representation in CLIPS/COOL 497

Application of a Rule-Based Knowledge System Using CLIPS

for the Taxonomy of Selected Opuntia Species 505

The Nutrition Advisor Expert System 511

NASA STB Bulletin Board

To obtain updated and detailed information on all software tools developed by the Software Technology Branch (STB), you may log onto the STB Bulletin Board. You will find software release information, abstracts, information make-files, ordering information, bug reports, work arounds, and much more. An option is also available to communicate with NASA technical staff via email options. Anyone can use the BBS whether they are a government user or not. Simply call up the BBS 24 hours a day, and create yourself an individual account.

STB BULLETIN BOARD

Logon: (713) 286-5375, OR (713) 286-7252

300, 1200, 2400 Baud, No Parity, 8 Data bits, 1 Stop Bit

Internet Mail Address (NOT THE STB BULLETIN BOARD): stbprod@fdr.jsc.nasa.gov

STB Help Desk (Voice): (713) 286-8919

STB Help Desk (FAX): (713) 286-4479

Software tools supported by the STB

CLIPS: A productive development and delivery expert system tool which provides a complete environment for the construction of rule and/or object based expert systems. CLIPS is the first language to provide a verification/validation utility for the development of expert systems. The key features of CLIPS are knowledge representation, portability, integration/extensibility, interactive development, and objects.

NETS: A software tool which provides an environment for the development and evaluation of neural networks. With NETS you can create and execute arbitrary configurations of neural networks which use the back propagation learning technique. NETS is portable and will run on a variety of machines from mainframes to personal computers.

COSTMODL: A software tool which automates the process of developing estimates of the effort and schedule required for the development of a software product. With COSTMODL, you can estimate development costs for a wide range of software products including incrementally developed programs and programs written in Ada.

Splicer: A genetic algorithm tool which can be used to solve search and optimization problems. Genetic algorithms are adaptive search procedures based loosely on the processes of natural selection and Darwinian "survival of the fittest." Splicer provides the underlying framework and structure for building a genetic algorithm application.

TARGET: A graphical interface tool that captures procedural knowledge and produces a task hierarchy report. The initial design of TARGET was based on a knowledge tool developed by the Naval Systems Training Center, called VISTA. Target is currently written in C and is available for the Microsoft Windows platform, with future platform ports to Macintosh and X-Windows.

Titles of CLIPS abstracts

Following is an index of the CLIPS APPLICATIONS ABSTRACTS . The ABSTRACTS contains brief descriptions volunteered by users of their applications that have either been created, or are in the process of being created. The abstracts are on the STB Bulletin Board.

warfare engagements 205

Index

A

B

C

D

E

F

G

H

I

K

L

M

N

O

P

Q

R

S

SYMBOL

| constraint, 60

T

U

V

W

 

[출처] https://www.csee.umbc.edu/portal/clips/usersguide/clipsusr.html

 

 

 

 

본 웹사이트는 광고를 포함하고 있습니다.
광고 클릭에서 발생하는 수익금은 모두 웹사이트 서버의 유지 및 관리, 그리고 기술 콘텐츠 향상을 위해 쓰여집니다.
번호 제목 글쓴이 날짜 조회 수
1048 File Encodeing Converter (파일 인코딩 일괄 변환기) file 졸리운_곰 2021.10.02 1
» CLIPS 6.0 User's Guide May 28, 1993 by Joseph C. Giarratano, Ph.D. file 졸리운_곰 2021.09.28 3
1046 [一日30分 인생승리의 학습법] [알쓸IT잡] 가상현실(VR), 증강현실(AR), 혼합현실(MR)을 아우르는 확장현실(XR, eXtended Reality) file 졸리운_곰 2021.09.23 5
1045 스프레드시트를 생산성 도구로...'구글 테이블' A to Z file 졸리운_곰 2021.09.17 5
1044 칼럼 | 하둡의 실패 넘어선다··· 오픈 데이터 분야를 견인하는 4가지 기술 동향 file 졸리운_곰 2021.09.17 2
1043 [一日30分 인생승리의 학습법] REST API 제대로 알고 사용하기 file 졸리운_곰 2021.09.06 7
1042 데이터를 가치있는 ‘자산’으로 만들기··· '5가지 지침' Martha Heller | CIO file 졸리운_곰 2021.09.02 9
1041 [CIOKorea] 데이터를 가치있는 '자산'으로 만들기 - '5가지 지침' 졸리운_곰 2021.09.02 3
1040 [一日30分 인생승리의 학습법] 짱 멋진 "머신러닝 라이브러리" 정리 file 졸리운_곰 2021.08.27 5
1039 Gitlab - SSL 적용 file 졸리운_곰 2021.08.27 3
1038 git 에서 https repository 연결시 SSL 인증서 오류 해결법 file 졸리운_곰 2021.08.27 10
1037 [GIT] Conflict(충돌) 났을 때 강제로 Pull 하기. 졸리운_곰 2021.08.24 3
1036 [一日30分 인생승리의 학습법] How to Run : Linux Containers on Windows Server 2019 file 졸리운_곰 2021.08.07 5
1035 [一日30分 인생승리의 학습법] [Tensorflow] Serving이용하여 REST API 만들기 file 졸리운_곰 2021.08.07 5
1034 [一日30分 인생승리의 학습법] Amazon SageMaker는 처음이지? 누워서 머신러닝 학습부터 배포까지 file 졸리운_곰 2021.08.05 2
1033 [一日30分 인생승리의 학습법] Apache Beam (Dataflow)를 이용하여, 이미지 파일을 tfrecord로 컨버팅 하기 file 졸리운_곰 2021.08.04 3
1032 [一日30分 인생승리의 학습법] [GCP] Apache Beam 사용하기 file 졸리운_곰 2021.08.04 2
1031 [一日30分 인생승리의 학습법] Apache Beam, Apache Airflow, Apache Atlas 설명 졸리운_곰 2021.08.04 3
1030 [一日30分 인생승리의 학습법] 블레이저 웹어셈블리 (web assembly, WASM_ Awesome Blazor ) 놀라운 오픈소스 리스트 (open source) file 졸리운_곰 2021.08.04 72
1029 MarkDown 사용법 총정리 file 졸리운_곰 2021.07.29 9
대표 김성준 주소 : 경기 용인 분당수지 U타워 등록번호 : 142-07-27414
통신판매업 신고 : 제2012-용인수지-0185호 출판업 신고 : 수지구청 제 123호 개인정보보호최고책임자 : 김성준 sjkim70@stechstar.com
대표전화 : 010-4589-2193 [fax] 02-6280-1294 COPYRIGHT(C) stechstar.com ALL RIGHTS RESERVED