Expert Systems 3 1

Rewriting Rules, CLIPS

Content of this lecture:1. Interpretation of rules2. Example: CLIPS Sorting3. Non-determinism4. Control regimes: Selection5. Conflict Resolution

Content of next lecture:1. Serious CLIPS: Language

Understanding2. Interpreter issue: Rete

CLanguageIntegratedProductionSystem

(NASA, 1985)

Expert Systems 3 2

Rules as Declarative Knowledge

Example of a declarative rule: IF X is a rabbit THEN X is four-legged

Meaning independent of program state.

Premisse: X is rabbitConclusion: X is four-legged

Procedural interpretation: IF the memory state

hasX stored as a rabbit

THEN update the state tomake X four-legged

When will this happen??

Rule gives Z-knowledge:

Rabbit

Non-four-legged

Four-legged

Non-Rabbit

Rabbit

We don’t know the situation when X is not a rabbit

Expert Systems 3 3

Conditional statement in programming

Form of conditional: if c if c then S1 then S1 else S2

Executed at some point;know exactly what happens!

Condition c at that moment gives action S1,

non c gives action S2.

Form of production rule:• Theoretical:

{c} S1

• Informal in Rule-based: IF c THEN S1But not conditional statement!

• In CLIPS:(defrule NAME c => S1)

Truth of c allows application of action S1

Expert Systems 3 4

What if more rules apply?

Life experiment with four volunteers

Describe the positions of these heroes

Expert Systems 3 5

Representation of facts: Relations

• Define table structure:(deftemplate neighbor (field left (type SYMBOL)) (field right (type SYMBOL)))

• Provide facts:(deffacts inputs (neighbor (left Anneke) (right Bert)) (neighbor (left Bert) (right Carol)) (neighbor (left Carol) (right Danny)))

Object, Attribute, Value

neighbor

left right

Anneke Bert

Carol Danny

Bert Carol

Table name Column name

Table content: 3 facts

Facts are numbered(time stamped)

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Numerical inputs for the volunteers

(deftemplate holds (field person (type SYMBOL)) (field number (type INTEGER)))

(holds (person Anneke) (number 17)) (holds (person Bert) (number 6)) (holds (person Carol) (number 7)) (holds (person Danny) (number 27))

holds

person number

Anneke 17Goal: put numbers in ordered sequence

Expert Systems 3 7

The sorting rule: swap

IF neighbor X YX holds aY holds bb > a

THEN X gets bY gets a

Procedural sorting knowledge:parties exchange their numbers when locally in wrong order

Expert Systems 3 8

The sorting rule in CLIPS

(defrule swap (neighbor (left ?X) (right ?Y)) ?Xhas <- (holds (person ?X) (number ?a)) ?Yhas <- (holds (person ?Y) (number ?b&:(> ?b ?a))) => (modify ?Xhas (number ?b)) (modify ?Yhas (number ?a)))

Rule name

Value condition

Value wildcard

Tuple wildcard

Action part modifies two existing facts

Value wildcard

Matching instantiation:Facts w. common value of X, Y, a, bDefines (binds) values for wildcards

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Non-determinism

• “Program determines behavior of Computer”• Sorting rule allows different behaviors depending on

chosen instantiation:Non-determinism

• Theorem 1: Each sequence of swaps is finite.

• Theorem 2: In any blocked situation, numbers are descending.

• Conclusion:Non-determinism is not necessarily a problem.

Expert Systems 3 10

The Recognize-Act Cycle

Rule interpretation is a three-stroke engine:

1. Match:Form Conflict Set by finding satisfied rule instances.

2. Choose:Select one instance from the conflict set by applying a Conflict Resolution strategy.

3. Apply:Modify memory according to selected rule.

Conflict set is usually formed explicitly.

“Happy”rule

Fact baseConflict set

(CLIPS: Agenda)

Match

ChooseApply

works as

Expert Systems 3 11

Beyond Sorting: Selection

Find the second largest number1. Sort the numbers;2. Find the person on position 2

(from neighbor relation);3. Output the number of person

on position 2.

Sequential programming: sort program ; indexer program ; output program.

Sorting Rules

Output Rules

Indexing Rules

Production rule set:

Expert Systems 3 12

Rules for indexing

(deftemplate index (field person (type SYMBOL)) (field place (type INTEGER)) )

(defrule pickfirst (neighbor (left ?X)) (not (neighbor (right ?X))) => (assert (index (person ?X) (place 1))) )

(defrule picknext (neighbor (left ?X) (right ?Y)) (index (person ?X) (place ?I)) => (assert (index (person ?Y) (place (+ ?I 1)))) )

Addobject

Absence of tuple cannot bind

wildcard

Clutter Logic in Parenthesis Spaghetti

Expert Systems 3 13

Rule for output

(defrule answer (index (person ?X) (place 2)) (holds (person ?X) (number ?A)) => (printout t crlf "The second greatest number is “ ?A "." t crlf ))

Summary of rules:• Sorting: swap• Indexing: pickfirst, picknext• Output: answerSee program select.clp and

play with it in the CLIPS interpreter

Expert Systems 3 14

Control the firing of rules

Conflict Resolution can be• Local control

Preference among rules is explicit in programStrategy is problem dependentEx. Meta-Rules (not in CLIPS)

Salience, Goal variable• Global control

Use built-in mechanism of interpreterBad adaptation to domain, but can select best oneEx. Depth, Breadth, Specificity,

MEA, LEX

(Non-determinism of the second type:not relevant for CLIPS.)

Expert Systems 3 15

Salience: Ordering on Rules

• Add in rule: (declare (salience 30))• Range -100 … 100, default 0.

• Selection program (selectSalience.clp):Sorting 30, indexing 20, output 10.

• Note: firing of rule may enable a rule of higher salienceHigher rule will be preferred in next cycle!Sorting gets high priority permanently!!

• No resolution among instantiations of same rule

• Easily overcontrolled:sorting and indexing can overlap

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Control with goal variable

• Simple variable has two names! (deftemplate goal (field phase (type SYMBOL)) )• Add condition to rules: (defrule answer (goal (phase output)) (index (person ?X) (place 2))• Explicit switch of goal (new rule!): (defrule endindexing ?c <- (goal (phase indexing)) (index (place 2)) => (modify ?c (phase output)) )• Ex.: selectGoal.clp.• Fine control over subtasks• Alternation possible

goal

phase

sorting

Table name

Column name

Table storage: multiple goals simultaneously

Expert Systems 3 17

Global control regimes

• Order in program

• Refraction: never repeat an instantiation. (defrule pickfirst (not (neighbor (right ?X))) => (assert (index (person ?X) (place 1))) )

Need not condition on uncomputed place• Recency: order by time tags of matching facts• Specificity: prefer instantiations with more facts bird => fly bird, penguin => not fly

Suitable for coding exceptions or shift of goal.

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Depth and Breadth

• Depth strategy:Prefer instantiations by new facts

• Breadth strategy:Prefer instantiations by old fact

Start state

QED

Expert Systems 3 19

Complexity used to switch subtasks

(defrule swap (goal sort) (neighbor ?X ?Y) ?Xs <- (holds ?X ?a) ?Ys <- (holds ?Y ?b>?a) => (modify ?Xs (number ?b)) (modify ?Ys (number ?a))

)

(defrule endsort ?c <- (goal sort) => (modify ?c indexing))

• Conditions of endsort less complex than swap

• Goal is changed only when no swap applies

• Explicit switch prevents later uncontrolled swapping (cp. with salience)

• Requires the global regime complexity to be selected!

Abbreviation!

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LEX (lexicographic)

• Each fact has time stamp• To choose from conflict set:

1. Dump all instantiations not using the most recent

fact present in the CS;

2. From remaining facts, drop this most recent fact

Repeat until choice is made.

• LEX implies Recency and Complexity

• MEA variation: first order by time stamp of fact in first condition of rule

Live experiment

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Summary and conclusions

• Production rules encode steps towards solution• Non-determinism results from collection of rules

• Local control regimes resolve conflicts by adding meta-knowledge to the program

• Eliciting and coding meta-knowledge is difficult• Knowledge and meta-knowledge are not well-separated

in rule-based program (CLIPS)

• Global control regimes use properties of the interpreter• Different global regimes cannot be combined

• Selection is not a typical Expert System task!• Next class (4): Language understanding