expert systemsnov 04, 2019  · popular expert systems • pxdes –is a expert system that uses an...

Budditha Hettige

Department of Computer Engineering

Faculty of Computing

General Sir John Kotelawala Defence University

SOURCE : Building Expert Systems in Prolog, Dennis Merritt

Expert Systems

Overview

• What is an Expert System?

• What are the Expert system features?

• Steps to Expert System development

– Knowledgebase

– User Interface

– Shell

• Prolog Java Interface (JPL)

• Prolog Web Interface

• Examples

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Expert System

• Computer applications which embody some non-

algorithmic expertise for solving certain types of

problems

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{Dennis Merritt}

Advantages

• Easy to develop and modify

• The use of satisficing (accepting satisfactory solution rather than the optimal one)

• The use of heuristics

• Development by knowledge engineers and users

• Goal driven reasoning or backward chaining

• Coping with uncertainty

• Data driven reasoning or forward chaining

• Data representation

• User interface

• Explanations

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Limitations of Expert Systems

• Limited to relatively narrow problems

• Cannot readily deal with “mixed” knowledge

• Possibility of error

• Cannot refine own knowledge base

• Difficult to maintain

• May have high development costs

• Raise legal and ethical concerns

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Applications of Expert Systems• Credit granting

• Information management and retrieval

• AI and expert systems embedded in products

• Plant layout

• Hospitals and medical facilities

• Help desks and assistance

• Employee performance evaluation

• Loan analysis

• Virus detection

• Repair and maintenance

• Shipping

• Marketing

• Warehouse optimization

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Participants in Expert Systems

Development and Use

• Domain expert– The individual or group whose expertise and knowledge is

captured for use in an expert system

• Knowledge user– The individual or group who uses and benefits from the

expert system

• Knowledge engineer– Someone trained or experienced in the design,

development, implementation, and maintenance of an expert system

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Evolution of Expert Systems Software

• Expert system shell

– Collection of software packages & tools to design,

develop, implement, and maintain expert systems

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Expert Systems Development

Alternatives

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Popular Expert Systems

• PXDES

– Is a expert system that uses an inference engine to determine the type and degree of pneumoconiosis, or lung cancer

– Uses X-rays to look at shadows on the lungs

• MyCIN

– MYCIN was an early backward chaining expert system

– Operated using fairly simple inference engine, and a knowledge base of ~600 rules

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Steps to

Expert System Development

• Identify the problem

• Build up Knowledge base

– Fats

– Rules

– Expirations

• Build up Inference Engine

– Way to sole problem

• Design a user Interface

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Identify the problem

• Input

– What are the Questions?

– What is the order of the Questions?

• Output

– What is the final result(s)?

• Facts

– What are the fats requires to collect the answers?

• Explanations

– In case, what are the explanations?

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Build up Knowledgebase

• What are the facts?

• What are the rules?

• How they represents?

• Example

family(duck):-

order(waterfowl), feed(on_water_surface), flight(agile).

bird(mallard):- family(duck), voice(quack), head(green).

bird(mallard):- family(duck), voice(quack), color(mottled_brown).

bird(pintail):- family(duck), voice(short_whistle).

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Build up Inference Engine

• Prolog has a built-in backward chaining inference engine that can be used to partially implement some expert systems

• The rules for expert systems are usually written in the form:

– bird(pintail):- family(duck), voice(short_whistle).

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User Interface

• The system can be dramatically improved by

providing a user interface

• Identify Attribute and values for the each case

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Ask Questions

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Menu for a user

• Example:

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Remembering the answer

• Example:

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Expert System Shell

• Architecture of the Native shell.

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The Shell

• The shell will seek to solve a generic predicate called

top_goal.

top_goal(X) :- bird(X).

• The shell has a predicate called solve, which does some

housekeeping and then solves for the top_goal.

• Example

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Explanation

• Expert systems have ability to explain theirbehavior.

• This means the user can ask the system for justification of conclusions or questions at any point in a consultation with an expert system

• Types of Explanation

– A rule trace, which reports on the progress of a consultation;

– Explanation of how the system reached a given conclusion;

– Explanation of why the system is asking a question;

– Explanation of why not a given conclusion.

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Explanation (Questions)

The why questions occur at the bottom of an inference

chain, and the how questions occur at the top

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Java Prolog Interface

• SET PATH for the swipl.exe

– C:\Program Files (x86)\swipl\bin

• Add jpl.jar to your project

• Create suitable prolog source file

• Add prolog source file into your java project folder

• Import jpl and complete your development

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Java Codes for Prolog connection

• Import JPL libraryimport org.jpl7.JPL;

import org.jpl7.Query;

import org.jpl7.Term;

• Collect JPL information

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JPL Code

• Consult prolog sourceString t1 = "consult('family.pl')";System.out.println(t1 + " " + (Query.hasSolution(t1) ? "succ" : "failed"));

• Run Prolog predicate String t2 = "child_of(joe, ralf)";

System.out.println(t2 + " is " + (Query.hasSolution(t2) ? "pro" : "not"));

• Get one solutionString t4 = "descendent_of(X, ralf)";

System.out.println("first solution of " + t4 + ": X = " +

Query.oneSolution(t4).get("X"));

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JPL Code (2)

String t4 = "descendent_of(X, ralf)";

Map<String,Term>[] ss4 =

Query.allSolutions(t4);

System.out.println("all solutions of " + t4);

for (int i = 0; i < ss4.length; i++)

{

System.out.println("X = " + ss4[i].get("X"));

}

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JPL Code (3)

String t5 = "descendent_of(X,Y)";

Query q5 = new Query(t5);

System.out.println("each solution of " + t5);

while (q5.hasMoreSolutions())

{

Map<String, Term> s5 = q5.nextSolution();

System.out.println("X = " + s5.get("X") + ",

Y = " + s5.get("Y"));

}

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Example (relation.pl)

male(somapala).

male(gunapala).

male(rathnapala).

female(seela).

female(susila).

female(neetha).

parent(seela,kamal).

parent(seela,nayana).

parent(seela,saman).

parent(somapala,kamal).

parent(somapala,nayana).

parent(somapala,saman).

parent(kamal,sanjaya).

parent(ruvani,sanjaya).

parent(saman,susi).

parent(saman,yasith).

parent(saman,oshan).

parent(kumari,susi).

parent(kumari,yasith).

parent(kumari,oshan).

print:-write('how are you').

print(X):- write('Anwer is '),write(X),nl.

print(X,Y):- write('Anwer is '),write(X), write(Y),nl.

mother(X,Y):-female(X),parent(X,Y).

father(X,Y):-male(X),parent(X,Y).

son(X,Y):- male(X),parent(Y,X).

whois(X, Y) :- mother(X,Y), write(X), write(' is mother of'), write(Y).

whois(X, Y) :- father(X,Y), write(X), write(' is father of'), write(Y).

whois(X, Y) :-

son(X,Y), write(X), write(' is son of'), write(Y).

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Example:

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Activity

• Create an expert system to select a suitable A/L

stream

– What should be the output

– Questions

– Order of the questions

– Input methods

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