rulebase forward and backwardcahning digram

8/8/2019 Rulebase Forward and Backwardcahning Digram

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Basic Architecture of an Expert System


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Knowledge base - contains the domain specific problem-solving

knowledge.

Facts - represent what we know at any time about the problem

we are working at.

Rules - represent relationships between the facts.

Inference engine - is a general program that activates the knowledgein the knowledge base.

Interface enables the user to communicate with the expert system.


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Rule-Based Expert Systems

Based on the production system concept.

Rules

IF the engine is getting gas

AND the engine will turn over

THEN the problem is spark plugs

Facts

The engine is getting gas

Conclusion: action

employ a particular model

execute a procedure

display a report


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Inference Engine

(1) Selection of rule candidates: pattern matching

(2) Choice of one rule: conflict resolution

(3) Execution: deduction


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Backward chaining (goal driven): the inference engine works

backward from a conclusion to be proven to determine if there

are data in the workspace to prove the truth of the conclusion.

Example.

Rule base Workspace

R1: IF A AND B THEN DA,B

R2: IF B THEN C

R3: IF C AND D THEN E


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Example. Expert system for diagnosing car problems.

Rule 1: IF the engine is getting gasAND the engine will turn over

THEN the problem is spark plugs

Rule 2: IF the engine does not turn over

AND the lights do not come onTHEN the problem is battery or cables.

Rule 3: IF the engine does not turn over

AND the lights do come on

THEN the problem is the starter motor.

Rule 4: IF there is gas in the fuel tank

AND there is gas in the carburettor

THEN the engine is getting gas


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The problem is X

Rule 1

Rule 2

Rule 3

Rule 4

the engine is

getting gas

the engine willturn over

the problem is

spark plugs

Rule 1

Rule 2

Rule 3Rule 4

Working space

Working space


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gas in fuel tank

gas in carburettor

the engine is

getting gas

the engine will

turn over

the problem is

spark plugs

Rule 1Rule 2

Rule 3

Rule 4

Working space


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Explanation in Backward Chaining

Why?

gas in fuel tank?

yes

gas in carburettor?

yes

engine will turn over?

why

It has been established that:

1. the engine is getting gas,

therefore if2. the engine will turn over,

then the problem is spark plugs


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How?

how the engine is getting gas

This follows from rule 4:

IF there is gas in the fuel tank

AND there is gas in the carburettorTHEN the engine is getting gas

gas in fuel tank was given by the user

gas in carburettor was given by the user


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Exercise.

Rule 1 IF blood pressure is likely to be high

THEN risk of heart failure is high

Rule 2 IF blood pressure is likely to be lowTHEN risk of heart failure is low

Rule 3 IF alcohol consumption is high

AND patient salt intake is high

THEN blood pressure is likely to be high

Rul

e 4 IF alcohol consumption is lowAND patient salt intake is low

THEN blood pressure is likely to be low

Rule 5 IF units of alcohol per week are > 30

THEN alcohol consumption is high

Rule 6 IF units of alcohol per week are < 20

THEN alcohol consumption is lowRule 7 IF units of alcohol per week are >= 20 AND


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Forward chaining (data driven): the inference engine works from

the initial content of the workspace towards the final conclusion.

Example.

Rule base Workspace

R1: IF A AND B THEN DA,B

R2: IF B THEN C

R3: IF C AND D THEN E


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Rule 1

Rule 2

Rule 3Rule 4

the engine

turns over

Rule 1

Rule 2

Rule 3

Rule 4

Working space

Working space

Example. Expert system for diagnosing car problems.


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The engine is

getting gas

There is gas

in the fuel tank

There is gas

in the carburettor

The engine

turns over

Rule 1Rule 2

Rule 3

Rule 4

Working space


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Explanation in Forward Chaining

Why?

The current rule under consideration is presented.

How?

More difficult than in backward chaining.


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ExampleR1: IF management competence is good

AND External credit rating is fair

AND Bank's credit rating is marginalTHEN Loan is rejected

R2: IF Loan type is seasonal

AND Profitability rating is high

AND Solvency rating is low

THEN Bank's credit rating is marginal

R3: IF Cash/current liabilities > 0.1

AND Tentative solvency rating is low

THEN Solvency rating is low

Bank's credit rating UNKNOWN

Cash/current liabilities 0.18

External credit rating FAIR Loan SEASONAL

Loan type UNKNOWN

Management competence UNKNOWN

Profitability rating HIGH

Solvency rating UNKNOWN

Tentative solvency rating LOW


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Choosing between backward and forward chaining.


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Hybrid Expert System Architecture


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Example 1.

IF WEIGHT of MY-FORD > 3,000 pounds

THEN set DETOUR AROUND RICKETY BRIDGE

Example 2.

IF ?VEHICLE is instance-of AUTOMOBILES

AND ?VEHICLE has-a ?ENGINEAND ?ENGINE is instance-of DIESEL

THEN set REFUEL of?VEHICLE to TRUCKSTOP


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SUMMARY

The major components of an expert system are the knowledge base,inference engine, and user interface.

Rule-based expert systems are introduced.

There are two approaches for controlling inference in rule-basedexpert systems: forward chaining and backward chaining.

rulebase forward and backwardcahning digram

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