The CLIPS - PowerPoint Presentation

Slide1

The CLIPS Expert System Shell

Dr Nicholas Gibbins

nmg@ecs.soton.ac.ukSlide2

The CLIPS Expert System Shell

A framework for building expert systems

Don’t need to build basic infrastructure every time you build an expert system

Commonly used and well-understood

First developed at NASA JSC in mid-1980s

Provides the following facilities:

Representation of facts and rules

Search mechanism for identifying and firing matching rulesSlide3

Facts in CLIPS

Represented in CLIPS by s-expressions:

(likes fred sally)

likes

,

fred

and

sally

are symbols

Two types of CLIPS fact

Ordered (as above)

Unordered, specified using

deftemplate

(we’ll come to this later)Slide4

Starting and stopping CLIPS

Run CLIPS from the UNIX command line:

CLIPS>

To quit CLIPS, type

(exit)Slide5

Asserting facts

Add a new fact to the knowledge base with

assert

:

CLIPS> (assert (likes fred mary))

<Fact-0>

CLIPS>

Check for asserted facts with

facts

:

CLIPS> (facts)

f-0 (likes fred mary)

For a total of 1 fact.

CLIPS>

The

0

in

f-0

and

Fact-0

is the fact-index of the new factSlide6

Retracting facts

Remove a fact from the knowledge base with retract:

CLIPS> (assert (likes fred mary))

<Fact-0>

CLIPS> (facts)

f-0 (likes fred mary)

For a total of 1 fact.

CLIPS> (retract 0)

CLIPS> (facts)

CLIPS>

Note that you need to know the fact-index to retract a fact

Remove all facts from the knowledge base using

(clear)Slide7

Watching the knowledge base

Observe the activity in the knowledge base using

watch

:

CLIPS> (watch facts)

CLIPS> (assert (likes fred mary))

==> f-0 (likes fred mary)

<Fact-0>

CLIPS> (retract 0)

<== f-0 (likes fred mary)

CLIPS>

==>

indicates that a fact is being added

<==

indicates that a fact is being removed

Turn off watch using

(unwatch facts)Slide8

Creating rules

A simple rule:

(defrule mary-loved

(likes fred mary)

=>

(assert (loved mary)))

The name of the rule

The rule condition

The rule actionSlide9

Rules in general

(defrule <rule name> “optional comment”

<rule condition 1>

<rule condition 2

...

=>

<rule action 1>

<rule action 2>

...)

Everything before

=>

is known as the

left-hand side

(LHS), everything after the

right-hand side

(RHS)

The rule is fired if all of the conditions in the LHS match

When the rule fires, all of the actions are carried outSlide10

The Agenda

The list of rules which are waiting to be fired (the conflict set) is known as the agenda

This can be examined using

(agenda)

:

CLIPS> (agenda)

0 mary-loved: f-0

For a total of 1 activation.

CLIPS>Slide11

Running your rules

Start executing your rules with run:

CLIPS> (run)

==> f-1 (loved mary)

CLIPS>

Execution continues until there are no rules left to be fired (the agenda is empty)

Can control number of rule firings with

(run <number>)

Slide12

Variables

We can have variables in the conditions of our rules:

(defrule loved

(likes ?sub ?obj)

=>

(assert (loved ?obj)))Slide13

Variables

CLIPS> (assert (likes fred mary))

==> f-0 (likes fred mary)

<Fact-0>

CLIPS> (assert (likes fred sue))

==> f-1 (likes fred sue)

<Fact-1>

CLIPS> (agenda)

0 loved: f-1

0 mary-loved: f-0

0 loved: f-0

For a total of 3 activations.

CLIPS> (run)

==> f-2 (loved sue)

==> f-3 (loved mary)

CLIPS> Slide14

Loading from files

If your rules are defined in a file called

myrules.clp

At the shell command line:

$ clips -f myrules.clp

At the CLIPS command line:

CLIPS> (load “myrules.clp”)Slide15

Retracting facts

(defrule remove-liked

?fact <- (likes ?sub ?obj)

=>

(retract ?fact))

<-

binds the address of a matching fact to a variableSlide16

Anonymous variables

If we’re not interested in the value of a variable, we can match using a single-field wildcard variable:

?

(defrule remove-liked

?fact <- (likes ? ?)

=>

(retract ?fact))Slide17

Multifield variables

Consider a knowledge base with variable-length facts of the form

(route town-1 town-2 town-3 … town-n)

If we wish to match all routes that start at A and end at B, we can match all the intermediate towns using a multifield wildcard:

$?

Multifield variables match a list of objects (…)

(defrule find-route

(route town-a $?towns town-b)

=>

(printout t “Route from A to B via “ ?towns crlf))Slide18

Multifield variables

We have a fact:

(route a b c d e f g h)

In how many ways can this be matched by this pattern?

(route $?start ?item $?end)Slide19

Multifield variables

$?start = (), ?item = a, $?end = (b c d e f g h)

$?start = (a), ?item = b, $?end = (c d e f g h)

$?start = (a b), ?item = c, $?end = (d e f g h)

$?start = (a b c), ?item = d, $?end = (e f g h)

$?start = (a b c d), ?item = e, $?end = (f g h)

$?start = (a b c d e), ?item = f, $?end = (g h)

$?start = (a b c d e f), ?item = g, $?end = (h)

$?start = (a b c d e f g), ?item = h, $?end = ()Slide20

Field Constraints

We can further constraint the values taken by variables

~symbol

matches anything but

symbol

symbol1|symbol2

matches either

symbol1

or

symbol2

symbol1&symbol2

matches both symbols

?var&constraint matches anything that satisfies the constraint, and assigns it to ?varSlide21

Test Conditions

LHS of rule can contain other sorts of constraints on variable values (see BPG p. 47)

For example:

(defrule my-rule

(age fred ?var1)

(age sally ?var2)

(test (> ?var1 ?var2))

=>

…

)Slide22

Functions

CLIPS has a number of built-in functions which can be invoked like their Scheme look-a-likes:

(+ 1 2)

Complete list of built-in functions starting at p.149 of the CLIPS reference manual (Basic Programming Guide) Slide23

Defining functions

We can define a custom function using deffunction:

(deffunction square

(?x)

(* ?x ?x))Slide24

Defining functions

(deffunction function-name

(?arg1 ?arg2 ... $?args)

(action1

action2

...

actionn))

Value returned by function is that of last action

Final argument may be a multifield variableSlide25

Binding variables

We can bind the result of a function to a variable:

(bind ?sum (+ ?x ?y))Slide26

Example: Route Finding

E

C

B

D

A

5

7

4

2

8

3Slide27

Example: Route Finding

Represent routes as facts of the form:

(route

start

… end distance

)

For example:

(route town-a town-b town-d town-e 16)

How can we generate all of the shortest routes from every town to every other town?Slide28

Writing output

We can write to stdout using printout:

(defrule print-likes

(likes ?x ?y)

=>

(printout t ?x “ likes “ ?y crlf))

prints:

“john likes sally”Slide29

Reading input

(defrule read-colour

(initial-fact)

=>

(printout t “Name a colour” crlf)

(assert (colour (read))))

(read)

reads a single symbol, integer or string

(readline)

reads until the next carriage returnSlide30

Templated facts

The ordered lists of terms we’ve seen so far are only one kind of fact

We can also create facts containing unordered (but named) terms:

(car (colour red) (doors 4) (maker vw))

is the same as:

(car (doors 4) (maker vw) (colour red))Slide31

Templated facts

We introduce a new type of templated fact as follows:

(deftemplate car

(slot registration

(type SYMBOL))

(slot color

(type SYMBOL)

(allowed-symbols white red green blue))

(slot doors

(type INTEGER)

(default 4))

(slot maker

(type SYMBOL)))Slide32

Templated facts

Templated facts are asserted like any other fact:

(assert (car (registration g885tnj)

(doors 4)

(maker vw)

(colour green)))Slide33

Example: Classification

We wish to build an expert system to classify the following farmyard animals:

Dog

Cows

Chickens

Ducks

PigsSlide34

Example: Classification

Possible means for classification:

Fur/feathers/skin

Number of legs

Swims/doesn’t swim

Eats meat/grass/grainSlide35

Example: Classification

(deftemplate observation

(slot name

(type SYMBOL))

(slot value))

(deftemplate classification

(slot name

(type SYMBOL)))