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EXPERT SYSTEM

By,SAJNA FATHIMASMBS,MG UNIVERSITY

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DEFINITIONS

•An expert system is a computer program conceived to simulate some forms of human

reasoning (by the intermediary of an inference engine) and capable to manage an

important quantity of specialized knowledge.

•A system that uses human knowledge captured in a computer to solve problems that

ordinarily require human expertise (Turban & Aronson, 2001).

•A computer program designed to model the problem solving ability of a human expert

(Durkin, 1994).

•An intelligent computer program that uses knowledge and inference procedures to

solve problems that was difficult enough to acquire significant human expertise for

their solutions (Feigenbaum).

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OVERVIEW OF AN EXPERT SYSTEM

Can…

• Explain their reasoning or suggested decisions

• Display intelligent behavior

• Draw conclusions from complex relationships

• Provide portable knowledge

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COMPONENTS OF AN EXPERT SYSTEM

•User interface – the mechanism by which the user and the expert system

communicate.

•Explanation facility – explains the reasoning of the system to a user.

•Working memory – a global database of facts used by the rules.

•Inference engine – makes inferences by deciding which rules are satisfied by facts or

objects, prioritizes the satisfied rules, and executes the rule with the highest priority.

•Agenda – a prioritized list of rules created by the inference engine, whose patterns are

satisfied by facts or objects in working memory.

•Knowledge acquisition facility – an automatic way for the user to enter knowledge in

the system instead of having the knowledge engineer explicitly code the knowledge.

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STRUCTURE OF A RULE BASED EXPERT SYSTEM

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The knowledge base is also called the production memory in a rule-based expert

system.

As a simple example, consider the problem of deciding to cross a street. The

productions for the two rules are as follows, where the arrows mean that the system will

perform the actions on the right of the arrow if the conditions on the left are true.

the light is red -> stop

the light is green -> go

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The production rules can be expressed in an equivalent pseudocode IF... THEN

format as:

Rule: Red_light 

IF

the light is red

THEN 

            stop

Rule: Green_light 

IF 

        the light is green 

THEN 

        go

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•Two general methods of inference are commonly used as the problem-solving

strategies of expert systems: forward chaining and backward chaining. 

•FORWARD CHAINING - reasoning from facts to the conclusions resulting from those

facts. For example, if you see that it is raining before leaving home (the fact) then you

should take an umbrella (the conclusion).

•BACKWARD CHAINING – It involves reasoning in reverse from a hypothesis, a

potential conclusion to be proved, to the facts that support the hypothesis. For example,

if you have not looked outside and someone enters with wet shoes and an umbrella,

your hypothesis is that it is raining.

•In order to support this hypothesis you could ask the person if it was, in fact, raining. If

the response is yes, then the hypothesis is proved true and becomes a fact.

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•The working memory may contain facts regarding the current status of the traffic light

such as "the light is green" or "the light is red."

•Either or both of these facts may be in working memory at the same time.

• If the traffic light is working normally, only one fact will be in memory.

•As Expert Systems evolved many new techniques were incorporated into various types

of inference engines. Some of the most important of these were:

Truth Maintenance

Hypothetical Reasoning

Fuzzy Logic

Ontology Classification

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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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Expertsystem

Knowledge engineer

Knowledge userDomain expert

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ADVANTAGES

Easy to develop and modify

The use of satisficing

The use of heuristics

Development by knowledge engineers and users

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LIMITATIONS

•Not widely used or tested•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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THANK YOU