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.