expert system and decision making

7/29/2019 expert system and decision making

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EXPERT SYSTEM

AND DECISION

MAKING

- Parul Jain


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INTRODUCTION

Artificial intelligence-based computerprograms called Expert Systems havereceived a great deal of attention.

They are used in a huge variety of fields

like medicine, mathematics, engineering,computer science and education etc.

An expert system stores the knowledgeof one or more human experts in a

particular field. ES are used for problems for which there

is no single "correct" solution which canbe encoded in a conventional algorithm.


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EXPERT SYSTEM

COMPONENTS The part of the expert system that

stores the knowledge is called the

knowledge base.

The part that holds the specifics of theto-be-solved problem is called the

global database

The part that applies the knowledge tothe problem is called the inference

engine.


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How to build an ES?

A knowledge engineer starts byreading domain-related literature tobecome familiar with the issues and

the terminology. holds extensive interviews with one or

more domain experts to "acquire" theirknowledge.

organizes the results of theseinterviews and translates them intosoftware that a computer can use.


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How to build an ES? (cont)


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CHARACTERSTICS

Operates as an interactive system Tools have ability to filter knowledge

Make logical inferences based on

knowledge storedAbility to Explain Reasoning

Domain-Specific

Applications Cost-effective alternative to Human

Expert


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FEATURES

Goal driven reasoning or backwardchaining

Coping with uncertainty

Data driven reasoning or forwardchaining

Data representation

User interface

Explanations


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EXPERT SYSTEMS ANDARTIFICIAL INTELLIGENCE

AI programs that achieve expert-levelcompetence in solving problems in task areasby bringing to bear a body of knowledgeabout specific tasks are called knowledge-basedorexpert systems.

The area of human intellectual endeavour tobe captured in an expert system is called thetask domain.

Taskrefers to some goal-oriented, problem-

solving activity. Domainrefers to the area within which the

task is being performed.

The Turing Test


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THE WORKING OF ES

Every expertsystem consists of

two principal parts:

the knowledge

base; and the

inference engine.

The knowledge

baseof expertsystems contains

both factual and

heuristic

knowledge.


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The working of ES (cont.)

Factual knowledgeis that knowledge

that is widely shared found in

textbooks or journals, and agreedupon by those knowledgeable in the

particular field.

Heuristic knowledgeis the lessrigorous, more experiential, more

judgmental knowledge of

performance.


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KNOWLEDGEREPRESENTATION

Knowledge representation formalizes andorganizes the knowledge.

One representation is a ruleconsisting of an IF partand a THEN part.

Another representation, called the unitis based

upon a more passive view of knowledge. The problem-solving modelcontrols the steps

taken to solve the problem. forward chaining -If the chaining starts from a set of

conditions and moves toward some conclusion, the

method. backward chaining -If the conclusion is known but the path

to that conclusion is not known, then that is reasoningbackwards.

The more knowledge a system is given, the morecompetent it becomes.


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RULE BASED ES

Any rule consists of two parts: the IF

part, called the antecedent(condition)

and the THEN part called the

consequent(action).

IF antecedent

THEN consequent

The antecedent of a rule incorporates

two parts: an objectand its value.

A rule can have multiple antecedents

joined by the keywords AND or OR.


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INFERENCE ENGINE

The inference engine is the genericcontrol mechanism that applies the

knowledge present in the knowledge

base to the task-specific data to arrive atsome conclusion.

inference mechanisms that search

through the database and deduce results

in an organized manner:

Forward chaining

Backward chaining

Tree searches


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FORWARD AND BACKWARDCHAINING

Forward chaining - one proceeds froma given situation toward a desired goal,adding new assertions along the way.

Backward chaining - In this strategy,

one starts with the desired goal, andthen attempts to find evidence forproving the goal.

Eg. Rule 1: IF A and C THEN F

Rule 2: IF A and E THEN GRule 3: IF B THEN ERule 4: IF G THEN D


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TREE SEARCHES

A knowledge base can usually berepresented as a branching network ortree.

Two approaches: depth-first search. breadth-first search.

The depth-first search algorithm begins at anode that either represents the given data

(forward chaining) or the desired goal(backward chaining).

Breadth-first search starts by expanding all thenodes one level below the first node. Then itsystematically expands each of these nodes till

a solution is reached or the tree is completelyexpanded.


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Tree searches (cont.)


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INTELLIGENT EDITORS

An intelligent editor acts as an interfacebetween a domain expert and an ExpertSystem.

The editor has direct access to theknowledge in the Expert System and knows

the structure of that knowledge Through the editors, an expert can create,

modify and delete rules without knowledgeof the internal structure of the rules


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ADVANTAGES OF EXPERTSYSTEMS

Permanence

human experts may forget. Reproducibility many copies. Efficiency increased system output. Consistency similar transactions give

same output. Documentation permanent

documentation. Completeness all transactions can be

viewed. Timeliness Entry barriers for competitors. Differentiation


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DISADVANTAGES

Common sense

Creativity in unusual situations.

Learning

no adaptability.

Sensory Experience

Degradation not good when noanswer exists.


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APPLICATIONS

Diagnosis and Troubleshooting ofDevices and Systems of All Kinds. Eg5GL DOCTOR

Planning and Scheduling. Eg GATES

Configuration of ManufacturedObjects from Subassemblies.

Financial Decision Making. EgINSPECTOR

Knowledge Publishing Process Monitoring and Control Design and Manufacturing. Eg


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CONCLUSION

Problem solving is accomplished byapplying specific knowledge rather than

specific technique. This is a key idea in

expert systems technology.

It reflects the belief that human experts do

not process their knowledge differently from

others, but they do possess different

knowledge. With this philosophy, when onefinds that their expert system does not

produce the desired results, work begins to

expand the knowledge base, not to

reprogram the procedures.


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THANK YOU

expert system and decision making

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