1. Introduction to CLIPS

2. Expert Systems: Principles and Programming, Fourth Edition2 What is CLIPS? CLIPS is a multiparadigm programming language that provides support for: –Rule-based –Object-oriented –Procedural programming Syntactically, CLIPS resembles: –Eclipse –CLIPS/R2 –JESS

3. Expert Systems: Principles and Programming, Fourth Edition3 Other CLIPS Characteristics CLIPS supports only forward-chaining rules. The OOP capabilities of CLIPS are referred to as CLIPS Object-Oriented Language (COOL). The procedural language capabilities of CLIPS are similar to languages such as: –C –Ada –Pascal –Lisp

4. Expert Systems: Principles and Programming, Fourth Edition4 CLIPS Characteristics CLIPS is an acronym for C Language Integrated Production System. CLIPS was designed using the C language at the NASA/Johnson Space Center. CLIPS is portable – PC  CRAY.

5. Expert Systems: Principles and Programming, Fourth Edition5 CLIPS Notation Symbols other than those delimited by, [ ], or { } should be typed exactly as shown. [ ] mean the contents are optional and mean that a replacement is to be made. * following a description means that the description can be replaced by zero or more occurrences of the specified value.

6. Expert Systems: Principles and Programming, Fourth Edition6 CLIPS Notation Descriptions followed by + mean that one or more values specified by description should be used in place of the syntax description. A vertical bar | indicates a choice among one or more of the items separated by the bars.

7. Expert Systems: Principles and Programming, Fourth Edition7 Fields To build a knowledge base, CLIPS must read input from keyboard / files to execute commands and load programs. During the execution process, CLIPS groups symbols together into tokens – groups of characters that have the same meaning. A field is a special type of token of which there are 8 types.

8. Expert Systems: Principles and Programming, Fourth Edition8 Numeric Fields The floats and integers make up the numeric fields – simply numbers. Integers have only a sign and digits. Floats have a decimal and possibly “e” for scientific notation.

9. Expert Systems: Principles and Programming, Fourth Edition9 Symbol Fields Symbols begin with printable ASCII characters followed by zero or more characters, followed by a delimiter. CLIPS is case sensitive.

10. Expert Systems: Principles and Programming, Fourth Edition10 String Fields Strings must begin and end with double quotation marks. Spaces w/in the string are significant. The actual delimiter symbols can be included in a string by preceding the character with a backslash.

11. Expert Systems: Principles and Programming, Fourth Edition11 Address Fields External addresses represent the address of an external data structure returned by a user-defined function. Fact address fields are used to refer to a specific fact. Instance Name / Address field – instances are similar to facts addresses but refer to the instance rather than a fact.

12. Expert Systems: Principles and Programming, Fourth Edition12 Entering / Exiting CLIPS The CLIPS prompt is: CLIPS> This is the type-level mode where commands can be entered. To exit CLIPS, one types: CLIPS> (exit)  CLIPS will accept input from the user / evaluate it / return an appropriate response: CLIPS> (+ 3 4)   value 7 would be returned.

13. Expert Systems: Principles and Programming, Fourth Edition13 Facts and CLIPS To solve a problem, CLIPS must have data or information with which to reason. Each chunk of information is called a fact. Facts consist of: –Relation name (symbolic field) –Zero or more slots w/associated values

14. Expert Systems: Principles and Programming, Fourth Edition14 Example Fact in CLIPS

15. Expert Systems: Principles and Programming, Fourth Edition15 Deftemplate Before facts can be constructed, CLIPS must be informed of the list of valid slots for a given relation name. A deftemplate is used to describe groups of facts sharing the same relation name and contain common information.

16. Expert Systems: Principles and Programming, Fourth Edition16 Deftemplate General Format

17. Expert Systems: Principles and Programming, Fourth Edition17 Deftemplate vs. Ordered Facts Facts with a relation name defined using deftemplate are called deftemplate facts. Facts with a relation name that does not have a corresponding deftemplate are called ordered facts – have a single implied multifield slot for storing all the values of the relation name.

18. Expert Systems: Principles and Programming, Fourth Edition18 Adding Facts CLIPS store all facts known to it in a fact list. To add a fact to the list, we use the assert command.

19. Expert Systems: Principles and Programming, Fourth Edition19 Displaying Facts CLIPS> (facts) 

20. Expert Systems: Principles and Programming, Fourth Edition20 Removing Facts Just as facts can be added, they can also be removed. Removing facts results in gaps in the fact identifier list. To remove a fact: CLIPS> (retract 2) 

21. Expert Systems: Principles and Programming, Fourth Edition21 Modifying Facts Slot values of deftemplate facts can be modified using the modify command:

22. Expert Systems: Principles and Programming, Fourth Edition22 Results of Modification A new fact index is generated because when a fact is modified: –The original fact is retracted –The modified fact is asserted The duplicate command is similar to the modify command, except it does not retract the original fact.

23. Expert Systems: Principles and Programming, Fourth Edition23 Watch Command The watch command is useful for debugging purposes. If facts are “watched”, CLIPS will automatically print a message indicating an update has been made to the fact list whenever either of the following has been made: –Assertion –Retraction

24. Expert Systems: Principles and Programming, Fourth Edition24 Deffacts Construct The deffacts construct can be used to assert a group of facts. Groups of facts representing knowledge can be defined as follows: (deffacts [<optional] comment] * ) The reset command is used to assert the facts in a deffacts statement.

25. Expert Systems: Principles and Programming, Fourth Edition25 The Components of a Rule To accomplish work, an expert system must have rules as well as facts. Rules can be typed into CLIPS (or loaded from a file). Consider the pseudocode for a possible rule: IF the emergency is a fire THEN the response is to activate the sprinkler system

26. Expert Systems: Principles and Programming, Fourth Edition26 Rule Components First, we need to create the deftemplate for the types of facts: (deftemplate emergency (slot type)) -- type would be fire, flood, etc. Similarly, we must create the deftemplate for the types of responses: (deftemplate response (slot action)) -- action would be “activate the sprinkler”

27. Expert Systems: Principles and Programming, Fourth Edition27 Rule Components The rule would be shown as follows: (defrule fire-emergency “An example rule” (emergency (type fire)) => (assert (response (action activate-sprinkler-system))))

28. Expert Systems: Principles and Programming, Fourth Edition28 Analysis of the Rule The header of the rule consists of three parts: 1.Keyword defrule 2.Name of the rule – fire-emergency 3.Optional comment string – “An example rule”

29. Expert Systems: Principles and Programming, Fourth Edition29 Analysis of Rule If all the patterns of a rule match facts, the rule is activated and put on the agenda. The agenda is a collection of activated rules. The arrow => represents the beginning of the THEN part of the IF-THEN rule. The last part of the rule is the list of actions that will execute when the rule fires.

30. Expert Systems: Principles and Programming, Fourth Edition30 The Agenda and Execution To run the CLIPS program, use the run command: CLIPS> (run [ ])  -- the optional argument is the maximum number of rules to be fired – if omitted, rules will fire until the agenda is empty.

31. Expert Systems: Principles and Programming, Fourth Edition31 Execution When the program runs, the rule with the highest salience on the agenda is fired. Rules become activated whenever all the patterns of the rule are matched by facts. The reset command is the key method for starting or restarting. Facts asserted by a reset satisfy the patterns of one or more rules and place activation of these rules on the agenda.

32. Expert Systems: Principles and Programming, Fourth Edition32 What is on the Agenda? To display the rules on the agenda, use the agenda command: CLIPS> (agenda)  Refraction is the property that rules will not fire more than once for a specific set of facts. The refresh command can be used to make a rule fire again by placing all activations that have already fired for a rule back on the agenda.

33. Expert Systems: Principles and Programming, Fourth Edition33 Command for Manipulating Constructs The list-defrules command is used to display the current list of rules maintained by CLIPS. The list-deftemplates displays the current list of deftemplates. The list-deffacts command displays the current list of deffacts. The ppdefrule, ppdeftemplate and ppdeffacts commands display the text representations of a defrule, deftemplate, and a deffact, respectively.

34. Expert Systems: Principles and Programming, Fourth Edition34 Commands The undefrule, undeftemplate, and undeffacts commands are used to delete a defrule, a deftemplate, and a deffact, respectively. The clear command clears the CLIPS environment and adds the initialfact-defacts to the CLIPS environment. The printout command can also be used to print information.

35. Expert Systems: Principles and Programming, Fourth Edition35 Other Commands Load – allows loading of rules from an external file. Save – opposite of load, allows saving of constructs to disk

36. Expert Systems: Principles and Programming, Fourth Edition36 Commenting and Variables Comments – provide a good way to document programs to explain what constructs are doing. Variables – store values, syntax requires preceding with a question mark (i.e: ?example)

37. Expert Systems: Principles and Programming, Fourth Edition37 Fact Addresses, Single-Field Wildcards, and Multifield Variables A variable can be bound to a fact address of a fact matching a particular pattern on the LHS of a rule by using the pattern binding operator “ <- ”. Single-field wildcards can be used in place of variables when the field to be matched against can be anything and its value is not needed later in the LHS or RHS of the rule (?). Multifield variables and wildcards allow matching against more than one field in a pattern ($?)

38. Expert Systems: Principles and Programming, Fourth Edition38 Field Constraints In addition to pattern matching capabilities and variable bindings, CLIPS has more powerful pattern matching operators. Consider writing a rule for all people who do not have brown hair: –We could write a rule for every type of hair color that is not brown. –This involves testing the condition in a roundabout manner – tedious, but effective.

39. Expert Systems: Principles and Programming, Fourth Edition39 Field Constraints The technique for writing a rule for all non- brown hair colors implies that we have the ability to supply all hair colors – virtually impossible. An alternative is to use a field constraint to restrict the values a field may have on the LHS – the THEN part of the rule.

40. Expert Systems: Principles and Programming, Fourth Edition40 Connective Constraints Connective constraints are used to connect variables and other constraints. Not connective – the ~ acts on the one constraint or variable that immediately follows it. Or constraint – the symbol | is used to allow one or more possible values to match a field or a pattern. And constraint – the symbol & is useful with binding instances of variables and on conjunction with the not constraint.

41. Expert Systems: Principles and Programming, Fourth Edition41 Combining Field Constraints Field constraints can be used together with variables and other literals to provide powerful pattern matching capabilities. Example #1: ?eyes1&blue|green –This constraint binds the person’s eye color to the variable, ?eyes1 if the eye color of the fact being matched is either blue or green. Example #2: ?hair1&~black –This constraint binds the variable ?hair1 if the hair color of the fact being matched is not black.

42. Expert Systems: Principles and Programming, Fourth Edition42 Functions and Expressions CLIPS has the capability to perform calculations. The math functions in CLIPS are primarily used for modifying numbers that are used to make inferences by the application program.

43. Expert Systems: Principles and Programming, Fourth Edition43 Numeric Expressions in CLIPS Numeric expressions are written in CLIPS in LISP-style – using prefix form – the operator symbol goes before the operands to which it pertains. Example #1: 5 + 8 (infix form)  + 5 8 (prefix form) Example #2: (infix) (y2 – y1) / (x2 – x1) > 0 (prefix) (> ( / ( - y2 y1 ) (- x2 x1 ) ) 0)

44. Expert Systems: Principles and Programming, Fourth Edition44 Return Values Most functions (addition) have a return value that can be an integer, float, symbol, string, or multivalued value. Some functions (facts, agenda commands) have no return values – just side effects. Division results are usually rounded off. Return values for +, -, and * will be integer if all arguments are integer, but if at least one value is floating point, the value returned will be float.

45. Expert Systems: Principles and Programming, Fourth Edition45 Variable Numbers of Arguments Many CLIPS functions accept variable numbers of arguments. Example: CLIPS> (- 3 5 7)  returns 3 - 5 =-2 - 7 = -9 There is no built-in arithmetic precedence in CLIPS – everything is evaluated from left to right. To compensate for this, precedence must be explicitly written.

46. Expert Systems: Principles and Programming, Fourth Edition46 Embedding Expressions Expressions may be freely embedded within other expressions:

47. Expert Systems: Principles and Programming, Fourth Edition47 Summing Values Using Rules Suppose you wanted to sum the areas of a group of rectangles. –The heights and widths of the rectangles can be specified using the deftemplate: (deftemplate rectangle (slot height) (slot width)) The sum of the rectangle areas could be specified using an ordered fact such as: (sum 20)

48. Expert Systems: Principles and Programming, Fourth Edition48 Summing Values A deffacts containing sample information is: (deffacts initial-information (rectangle (height 10) (width 6)) (rectangle (height 7) (width 5) (rectangle (height 6) (width 8)) (rectangle (height 2) (width 5)) (sum 0))

49. Expert Systems: Principles and Programming, Fourth Edition49 Summing Values

50. Expert Systems: Principles and Programming, Fourth Edition50 The Bind Function Sometimes it is advantageous to store a value in a temporary variable to avoid recalculation. The bind function can be used to bind the value of a variable to the value of an expression using the following syntax: (bind )

51. Expert Systems: Principles and Programming, Fourth Edition51 I/O Functions When a CLIPS program requires input from the user of a program, a read function can be used to provide input from the keyboard:

52. Expert Systems: Principles and Programming, Fourth Edition52 Read Function from Keyboard The read function can only input a single field at a time. Characters entered after the first field up to the  are discarded. To input, say a first and last name, they must be delimited with quotes, “xxx xxx”. Data must be followed by a carriage return to be read.

53. Expert Systems: Principles and Programming, Fourth Edition53 I/O from/to Files Input can also come from external files. Output can be directed to external files. Before a file can be accessed, it must be opened using the open function: Example: (open “mydata.dat” data “r”) mydata.dat – is the name of the file (path can also be provided)

54. Expert Systems: Principles and Programming, Fourth Edition54 I/O from/to Files data – is the logical name that CLIPS associates with the file “r” – represents the mode – how the file will be used – here read access The open function acts as a predicate function –Returns true if the file was successfully opened –Returns false otherwise

55. Expert Systems: Principles and Programming, Fourth Edition55 Table 8.2 File Access Modes

56. Expert Systems: Principles and Programming, Fourth Edition56 Close Function Once access to the file is no longer needed, it should be closed. Failure to close a file may result in loss of information. General format of the close function: (close [ ]) (close data)  example

57. Expert Systems: Principles and Programming, Fourth Edition57 Reading / Writing to a File Which logical name used, depends on where information will be written – logical name t refers to the terminal (standard output device).

58. Expert Systems: Principles and Programming, Fourth Edition58 Predicate Functions A predicate function is defined to be any function that returns: –TRUE –FALSE Any value other than FALSE is considered TRUE. We say the predicate function returns a Boolean value.

59. Expert Systems: Principles and Programming, Fourth Edition59 The Test Conditional Element Processing of information often requires a loop. Sometimes a loop needs to terminate automatically as the result of an arbitrary expression. The test condition provides a powerful way to evaluate expressions on the LHS of a rule. Rather than pattern matching against a fact in a fact list, the test CE evaluates an expression – outermost function must be a predicate function.

60. Expert Systems: Principles and Programming, Fourth Edition60 Test Condition A rule will be triggered only if all its test CEs are satisfied along with other patterns. (test ) Example: (test (> ?value 1))

61. Expert Systems: Principles and Programming, Fourth Edition61 Predicate Field Constraint The predicate field constraint : allows for performing predicate tests directly within patterns. The predicate field constraint is more efficient than using the test CE. It can be used just like a literal field constraint – by itself or part of a complex field. The predicate field constraint is always followed by a function for evaluation (predicate function).

62. Expert Systems: Principles and Programming, Fourth Edition62 Return Value Constraint The return value constraint = allows the return value of a function to be used for comparison inside a pattern. The return value constraint must be followed by a function (not necessarily a predicate function). The function must have a single-field return value.

63. Expert Systems: Principles and Programming, Fourth Edition63 The OR Conditional Element Consider the two rules:

64. Expert Systems: Principles and Programming, Fourth Edition64 OR Conditional Element These two rules can be combined into one rule – or CE requires only one CE be satisfied:

65. Expert Systems: Principles and Programming, Fourth Edition65 The And Conditional Element The and CE is opposite in concept to the or CE – requiring all the CEs be satisfied:

66. Expert Systems: Principles and Programming, Fourth Edition66 Not Conditional Element When it is advantageous to activate a rule based on the absence of a particular fact in the list, CLIPS allows the specification of the absence of the fact in the LHS of a rule using the not conditional element:

67. Expert Systems: Principles and Programming, Fourth Edition67 Not Conditional We can implement this as follows:

68. Expert Systems: Principles and Programming, Fourth Edition68 Deftemplate Attributes CLIPS provides slot attributes which can be specified when deftemplate slots are defined. Slot attributes provide strong typing and constraint checking. One can define the allowed types that can be stored in a slot, range of numeric values. Multislots can specify min / max numbers of fields they can contain. Default attributes can be provided for slots not specified in an assert command.

69. Expert Systems: Principles and Programming, Fourth Edition69 Type Attribute Defines the data types can be placed in a slot Example: (deftemplate person (multislot name (type SYMBOL)) (SLOT AGE (TYPE integer))) Once defined, CLIPS will enforce these restrictions on the slot attributes name – must store symbols age – must store integers

70. Expert Systems: Principles and Programming, Fourth Edition70 Allowed Value Attributes CLIPS allows one to specify a list of allowed values for a specific type – 8 are provided: SymbolsStrings LexemesIntegers FloatsNumbers Instance-namesValues

71. Expert Systems: Principles and Programming, Fourth Edition71 Range Attributes This attribute allows the specification of minimum and maximum numeric values. Example: (deftemplate person (multislot name (type SYMBOL)) (slot age (type INTEGER) (range 0 ?VARIABLE)))

72. Expert Systems: Principles and Programming, Fourth Edition72 Salience CLIPS provides two explicit techniques for controlling the execution of rules: –Salience –Modules Salience allows the priority of rules to be explicitly specified. The agenda acts like a stack (LIFO) – most recent activation placed on the agenda being first to fire.

73. Expert Systems: Principles and Programming, Fourth Edition73 Salience Salience allows more important rules to stay at the top of the agenda, regardless of when they were added. Lower salience rules are pushed lower on the agenda; higher salience rules are higher. Salience is set using numeric values in the range - 10,000  +10,000 – zero is intermediate priority. Salience can be used to force rules to fire in a sequential fashion.

74. Expert Systems: Principles and Programming, Fourth Edition74 Salience Rules of equal salience, activated by different patterns are prioritized based on the stack order of facts. If 2+ rules with same salience are activated by the same fact, no guarantee about the order in which they will be place on the agenda.

75. Expert Systems: Principles and Programming, Fourth Edition75 Phases and Control Facts

76. Expert Systems: Principles and Programming, Fourth Edition76 Figure 9.2 Assignment of Salience for Different Phases

77. Expert Systems: Principles and Programming, Fourth Edition77 Implementation of System Approaches: 1.Embed the control knowledge directly into the rules. Example: Detection rules would include rules indicating when the isolation phase should be entered. Each group of rules would be given a pattern indicating in which phase it would be applicable.

78. Expert Systems: Principles and Programming, Fourth Edition78 Implementation 2.Use salience to organize the rules. 3.Separate the control knowledge from the domain knowledge. Each rule is given a control pattern that indicates its applicable phase. Control rules are then written to transfer control between the different phases.

79. Expert Systems: Principles and Programming, Fourth Edition79 Salience Hierarchy Salience hierarchy is a description of the salience values used by an expert system. Each level corresponds to a specific set of rules whose members are all given the same salience. When rules for detection / isolation / recovery are zero, salience hierarchy is:

80. Expert Systems: Principles and Programming, Fourth Edition80 Misuse of Salience Because salience is such a powerful tool, allowing explicit control over execution, there is potential for misuse. Well-designed rule-based programs should allow inference engine to control firings in an optimal manner. Salience should be used to determine the order when rules fire, not for selecting a single rule from a group of rules when patterns can control criteria for selection.

81. Expert Systems: Principles and Programming, Fourth Edition81 Rule of Thumb No more than seven salience values should ever be required for coding an expert system – bested limited to 3 – 4. For large expert systems, programmers should use modules to control the flow of execution – limited to 2 – 3 salience values.