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Seyed Hashem Davarpanah University of Science and Culture Expert systems CLIPS.

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1 Seyed Hashem Davarpanah University of Science and Culture Expert systems CLIPS

2 Motivation CLIPS is a decent example of an expert system shell – rule-based, forward-chaining system it illustrates many of the concepts and methods used in other XPS shells it allows the representation of knowledge, and its use for solving suitable problems

3 Introduction CLIPS stands for – C Language Implementation Production System forward-chaining – starting from the facts, a solution is developed pattern-matching – Rete matching algorithm: find ``fitting'' rules and facts knowledge-based system shell – empty tool, to be filled with knowledge multi-paradigm programming language – rule-based, object-oriented (Cool) and procedural

4 Rete Matching Algorithm An expert system might check each rule against the known facts in the knowledge base, firing that rule if necessary, then moving on to the next rule.rulefactsknowledge base For even moderate sized rules and facts knowledge-bases, this approach performs far too slowly. The Rete algorithm provides the basis for a more efficient implementation. A Rete-based expert system builds a network of nodes, where each node (except the root) corresponds to a pattern occurring in the left-hand-side (the condition part) of a rule.nodes The path from the root node to a leaf node defines a complete rule left-hand-side. Each node has a memory of facts which satisfy that pattern. As new facts are asserted or modified, they propagate along the network, causing nodes to be annotated when that fact matches that pattern. When a fact or combination of facts causes all of the patterns for a given rule to be satisfied, a leaf node is reached and the corresponding rule is triggered.root nodeleaf node

5 The CLIPS Programming Tool history of CLIPS – influenced by OPS5 and ART – implemented in C for efficiency and portability – developed by NASA, distributed & supported by COSMIC – runs on PC, Mac, UNIX, VAX VMS CLIPS provides mechanisms for expert systems – a top-level interpreter – production rule interpreter – object oriented programming language – LISP-like procedural language

6 Components of CLIPS rule-based language – can create a fact list – can create a rule set – an inference engine matches facts against rules object-oriented language (COOL) – can define classes – can create different sets of instances – special forms allow you to interface rules and objects [Jackson 1999]

7 Notation symbols, characters, keywords – entered exactly as shown: – (example) square brackets [...] – contents are optional: – (example [test]) pointed brackets (less than / greater than signs) – replace contents by an instance of that type – (example ) star * – replace with zero or more instances of the type – * plus + – replace with one or more instances of the type – + (is equivalent to * ) vertical bar | – choice among a set of items: – true | false

8 Invoke / Exit CLIPS entering CLIPS double-click on icon, or type program name(CLIPS) system prompt appears: CLIPS> exiting CLIPS at the system prompt CLIPS> type (exit) – Note: enclosing parentheses are important; they indicate a command to be executed, not just a symbol

9 Fields - Examples Fields (data types) float4.00, 2.0e+2, 2e-2 integer4, 2, 22 symbolAlpha24*, stringJohnny B. Good instance name[titanic], [PPK] Variables ?var, ?x, ?dayvariables for single field value $?namesvariable for multi-field value

10 CLIPS –Facts Facts a relation-name, an ordered sequence of values (ordered facts), or a set of (slot-name slot-value)-pairs (i.e. deftemplate- facts) examples: (today is Thursday) (person (name Johnny B. Good) (age 25))

11 Ordered Facts Ordered facts are facts defined without (explicit) template; the field-values are ordered. Examples: (number-list ) (today is Sunday)

12 Deftemplate Facts Deftemplate-facts are facts defined based on a template; slots can be arranged arbitrarily, there is no specific order. Define a template for describing a set of facts using deftemplate (record structure). Use deffacts to create a list of facts based on a template.

13 Examples of Facts ordered fact (person-name Franz J. Kurfess) deftemplate fact (deftemplate person "deftemplate example (slot name) (slot age) (slot eye-color) (slot hair-color))

14 Defining Facts Facts can be asserted CLIPS> (assert (today is sunday)) Facts can be listed CLIPS> (facts) f-0 (today is sunday) Facts can be retracted CLIPS> (retract 0) CLIPS> (facts) [Jackson 1999]

15 Instances an instance of a fact is created by (assert (person (name "Franz J. Kurfess") (age 46) (eye-color brown) (hair-color brown)) )

16 Initial Facts (deffacts kurfesses "some members of the Kurfess family" (person (name "Franz J. Kurfess") (age 46) (eye-color brown)(hair-color brown)) (person (name "Hubert Kurfess") (age 44) (eye-color blue)(hair-color blond)) (person (name "Bernhard Kurfess") (age 41) (eye-color blue)(hair-color blond)) (person (name "Heinrich Kurfess") (age 38) (eye-color brown)(hair-color blond)) (person (name "Irmgard Kurfess") (age 37) (eye-color green)(hair-color blond)) )

17 Usage of Facts adding facts – (assert +) deleting facts – (retract +) modifying facts – (modify ( )+ ) retracts the original fact and asserts a new, modified fact duplicating facts – (duplicate ( )+ ) adds a new, possibly modified fact inspection of facts – (facts) prints the list of facts – (watch facts) automatically displays changes to the fact list

18 Rules general format (defrule ["comment"] * ; left-hand side (LHS) ; or antecedent of the rule => *) ; right-hand side (RHS) ; or consequent of the rule

19 Rule Components rule header – defrule keyword, name of the rule, optional comment string rule antecedent (LHS) – patterns to be matched against facts rule arrow – separates antecedent and consequent rule consequent (RHS) – actions to be performed when the rule fires

20 Rule - Example (defrule birthday A persons birthday (person (name ?name) (age ?age)) (has-birthday ?name ?age) => (printout t Happy Birthday, ?name)) template fact ordered fact terminal rule name comment variables variabletextfunction

21 Examples of Rules simple rule (defrule birthday-FJK (person (name "Franz J. Kurfess") (age 46) (eye-color brown) (hair-color brown)) (date-today April-13-02) => (printout t "Happy birthday, Franz!") (modify 1 (age 47)) )

22 Wildcards question mark ? – matches any single field within a fact multi-field wildcard $? – matches zero or more fields in a fact

23 Salience We can use salience measures to prioritize rules. CLIPS provides a built-in method for prioritizing rules: (declare (salience value)) Salience values can range from to Default is 0. We can thus force the execution of one rule over another. We can implement sequencing of rules.

24 Rule Prioritization in Clips for example, consider the following rules... (forced order of execution)

25 Two Nifty Rules (defrule fire-first (declare (salience 30)) (priority first) => (printout t "Print First" crlf) ) (defrule fire-second (declare (salience 20)) (priority second) => (printout t "Print Second" crlf) )

26 Field Constraints not constraint ~ – the field can take any value except the one specified or constraint | – specifies alternative values, one of which must match and constraint & – the value of the field must match all specified values – mostly used to place constraints on the binding of a variable

27 Mathematical Operators basic operators ( +,-,*,/) and many functions (trigonometric, logarithmic, exponential) are supported prefix notation no built-in precedence, only left-to-right and parentheses test feature – evaluates an expression in the LHS instead of matching a pattern against a fact pattern connectives – multiple patterns in the LHS are implicitly AND -connected – patterns can also be explicitly connected via AND, OR, NOT user-defined functions – external functions written in C or other languages can be integrated – Jess is tightly integrated with Java

28 Examples of Rules more complex rule (defrule find-blue-eyes (person (name ?name) (eye-color blue)) => (printout t ?name " has blue eyes." crlf))

29 Example Rule with Field Constraints (defrule silly-eye-hair-match (person (name ?name1) (eye-color ?eyes1&blue|green) (hair-color ?hair1&~black)) (person (name ?name2&~?name1) (eye-color ?eyes2&~?eyes1) (hair-color ?hair2&red|?hair1)) => (printout t ?name1 " has "?eyes1 " eyes and " ?hair1 " hair."crlf) (printout t ?name2 " has "?eyes2 " eyes and " ?hair2 " hair."crlf))

30 Using Templates (deftemplate student a student record (slot name (type STRING)) (slot age (type NUMBER) (default 18))) CLIPS> (assert (student (name fred))) (defrule print-a-student (student (name ?name) (age ?age)) => (printout t ?name is ?age) ) [Jackson 1999]

31 An Example CLIPS Rule (defrule sunday Things to do on Sunday (salience 0); salience in the interval [ , 10000] (today is Sunday) (weather is sunny) => (assert (chore wash car)) (assert (chore chop wood)) ) [Jackson 1999]

32 Variables & Pattern Matching Variables make rules more applicable (defrule pick-a-chore (today is ?day) (chore is ?job) => (assert (do ?job on ?day)) ) if conditions are matched, then bindings are used [Jackson 1999]

33 Retracting Facts from a Rule (defrule do-a-chore (today is ?day); ?day must have a consistent binding ?chore <- (do ?job on ?day) => (printout t ?job done) (retract ?chore) ) a variable must be assigned to the item for retraction [Jackson 1999]

34 Procedural Control in Actions Procedural Control Elements can appear on the RHS of a rule or in message-handlers of classes. ( if then + [else + ]);; else-part optional ( while [do] * ]);; do not mandatory

35 Example – if-then-else (defrule special-age 18, 21, 100 (or (person (name ?name) (age ?age&18)) (person (name ?name) (age ?age&21)) (person (name ?name) (age ?age&100))) => (if (= ?age 18) then (printout t ?name can buy beer in Canada.) else (if (= ?age 21) then (printout t ?name can buy beer in the USA.) else (if (= ?age 100) then (printout t The major will visit ?name ))...)

36 Condition Patterns with Logical Connectives Complex Conditions with logical connectives: (or (pattern1) (pattern2)) Rule becomes active if one of the patterns matches. example: (or (birthday) (anniversary)) matches fact base with facts (birthday) or (anniversary) Equivalent for: and(is default) not existsto be fulfilled for one matching fact forallto be fulfilled for all facts which match based on first fact and variable binding

37 Complex Condition Elements - or (defrule report-emergency (or (emergency (emergency-type fire) (location ?building)) (emergency (emergency-type bomb) (location ?building)) ) => (printout t evacuate ?building) ) reports a building if there is a fire or bomb emergency in this building

38 Complex Condition Elements – exists (defrule emergency-report (exists (or (emergency (emergency-type fire)) (emergency (emergency-type bomb))) ) => (printout t There is an emergency. crlf ) ) prints one emergency-message if there is a fire or bomb emergency. (no further matching, firing, or printout)

39 Complex Condition Elements – forall (defrule evacuated-all-buildings (forall (emergency (emergency-type fire | bomb) (location ?building) ) (evacuated (building ?building))) => (printout t All buildings with emergency are evacuated crlf)) prints evacuated-message if for all buildings, which have a fire or bomb emergency, the building is evacuated.

40 Salience We can use salience measures to prioritize rules. CLIPS provides a built-in method for prioritizing rules: (declare (salience value)) Salience values can range from to Default is 0. We can thus force the execution of one rule over another. We can implement sequencing of rules.

41 Rule Prioritization in Clips for example, consider the following rules... (forced order of execution)

42 Two Nifty Rules (defrule fire-first (declare (salience 30)) (priority first) => (printout t "Print First" crlf) ) (defrule fire-second (declare (salience 20)) (priority second) => (printout t "Print Second" crlf) )

43 Manipulation of Constructs show list of constructs (list-defrules), (list-deftemplates), (list- deffacts) prints a list of the respective constructs show text of constructs (ppdefrule ), (ppdeftemplate ), (ppdeffacts ) displays the text of the construct (``pretty print'') deleting constructs (undefrule ), (undeftemplate ), (undeffacts ) deletes the construct (if it is not in use) clearing the CLIPS environment (clear) removes all constructs and adds the initial facts to the CLIPS environment

44 bind-function bind-function – explicitly binds value to variable (bind ?age (read)) stores value of single field which is read into single- field variable ?age (bind ?name (readline)) stores line which is read as STRING into single-field STRING-variable ?address (bind ?address (explode$ (readline))) explode$ splits line which is read as STRING into multifield-value which is stored in multislot-variable ?address

45 Open, Close File Open file for read/write: (open r) – is physical file-name (path) – is name used in program – r indicates read-access (w, r+) example: (open example.dat my-file r) (read my-file) Close file: (close )

46 Input – read, readline read – input of single field readline – input of complete (line as string) general: (read ) refers to file-name in program (read) keyboard is default read with bind-function to bind input to variable: (bind ?input (read)) (bind $?input (readline))

47 Input – read, readline (read / readline ) – default is keyboard/terminal – file has to be opened using (open r) is physical file-name (can include path) is name used in read command r indicates read-access example: (open example.dat example r) (read example) use with bind-function to bind input to variable

48 Output - printout (printout... ) ut terminal is standard uotherwise refers to a file-name file has to be opened using (open w ) – is physical file-name (can include path) – is name used in printout command vw indicates write-access example: (open example.dat my-output w ) (printout my-output ?name crlf)

49 Program Execution agenda – if all patterns of a rule match with facts, it is put on the agenda – (agenda) displays all activated rules salience – indicates priority of rules refraction – rules fire only once for a specific set of facts prevents infinite loops – (refresh ) reactivates rules

50 Execution of a Program (reset) prepares (re)start of a program: – all previous facts are deleted – initial facts are asserted – rules matching these facts are put on the agenda (run [ ]) starts the execution breakpoints – (set-break [ ]) stops the execution before the rule fires, continue with ( run ) – (remove-break [ ]) – (show-breaks)

51 Watching watching the execution – (watch ) prints messages about activities concerning a (facts, rules, activations, statistics, compilation, focus, all) – (unwatch ) turns the messages off

52 Watching Facts, Rules and Activations facts – assertions (add) and retractions (delete) – of facts rules – message for each rule that is fired activations – activated rules: matching antecedents – these rules are on the agenda

53 More Watching... statistics – information about the program execution – (number of rules fired, run time,... ) compilation (default) – shows information for constructs loaded by (load) Defining deftemplate:... Defining defrule:... +j=j – +j, =j indicates the internal structure of the compiled rules » +jjoin added » =j join shared – important for the efficiency of the Rete pattern matching network focus – used with modules – indicates which module is currently active

54 Defining Functions in CLIPS Uses a LISP or Scheme-like syntax (deffunction function-name (arg... arg) action... action) (deffunction hypotenuse (?a ?b) (sqrt (+ (* ?a ?a) (* ?b ?b)))) (deffunction initialize () (clear) (assert (today is sunday))) [Jackson 1999]

55 Defining Classes & Instances defining the class CAR (defclass car (is-a user) (name) (made-by)) defining an instance of CAR (make-instance corvette of car (made-by chevrolet)) [Jackson 1999]

56 Managing Instances Commands to display instances CLIPS> (instances) [corvette] of car CLIPS> (send [corvette] print) [corvette] of car (made-by chevrolet) Command to group instances (in a file) (definstances (corvette of car (made-by chevrolet)) (thunderbird of car (made-by ford))) [Jackson 1999]

57 Clearing & Resetting Instances deleting an instance CLIPS> (send [corvette] delete) deleting all instances CLIPS> (unmake-instance *) resetting creates an initial object CLIPS> (reset) CLIPS> (instances) [initial-object] of INITIAL-OBJECT [Jackson 1999]

58 Limitations of CLIPS single level rule sets – in LOOPS, you could arrange rule sets in a hierarchy, embedding one rule set inside another, etc loose coupling of rules and objects – rules can communicate with objects via message passing – rules cannot easily be embedded in objects, as in Centaur CLIPS has no explicit agenda mechanism – the basic control flow is forward chaining – to implement other kinds of reasoning you have to manipulate tokens in working memory [Jackson 1999]

59 Alternatives to CLIPS JESS – see below Eclipse – enhanced, commercial variant of CLIPS – has same syntax as CLIPS (both are based on ART) – supports goal-driven (i.e., backwards) reasoning – has a truth maintenance facility for checking consistency – can be integrated with C++ and dBase – new extension RETE++ can generate C++ header files – not related to the (newer) IBM Eclipse environment NEXPERT OBJECT – another rule- and object-based system – has facilities for designing graphical interfaces – has a script language for designing user front-end – written in C, runs on many platforms, highly portable [Jackson 1999]

60 JESS JESS stands for Java Expert System Shell it uses the same syntax and a large majority of the features of CLIPS tight integration with Java – can be invoked easily from Java programs – can utilize object-oriented aspects of Java some incompatibilities with CLIPS – COOL replaced by Java classes – a few missing constructs more and more added as new versions of JESS are released

61 CLIPS Summary notation – similar to Lisp, regular expressions facts – (deftemplate), (deffacts), assert / retract rules – (defrule...), agenda variables, operators, functions – advanced pattern matching input/output – (printout...), (read...), (load...) program execution – (reset), (run), breakpoints user interface – command line or GUI

62 Important Concepts and Terms – agenda – antecedent – assert – backward chaining – consequent – CLIPS – expert system shell – fact – field – forward chaining – function – inference – inference mechanism – instance – If-Then rules – JESS – knowledge base – knowledge representation – pattern matching – refraction – retract – rule – rule header – salience – template – variable – wild card

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