Chapter: Artificial Intelligence

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Explanation Based Learning

Extract general rules from examples

EXPLANATION BASED LEARNING

 

Extract general rules from examples

 

Basic idea

 

– Given an example, construct a proof for the goal predicate that applies using the background knowledge.

 

– In parallel, construct a generalized proof with variabilized goal.

 

– Construct a new rule, LHS with the leaves of the proof tree and RHS with the variabilized goal.

 

– Drop any conditions that are always true regardless of value of variables in the goal.

 

                     Any partial subtree can be use for the extracted general rule, how to choose?

 

                     Efficiency, Operationality, Generality

 

– Too many rules slows down reasoning

 

– Rules should provide speed increase by eliminating dead-ends and shortening the

 

proof

 

– As general as possible to cover the most cases

 

Tradeoffs, how to maximize the efficiency of the knowledge base?


                     Any partial subtree can be use for the extracted general rule, how to choose?

 

                     Efficiency, Operationality, Generality

 

– Too many rules slows down reasoning

 

– Rules should provide speed increase by eliminating dead-ends and shortening the proof

 

– As general as possible to cover the most cases

 

Study Material, Lecturing Notes, Assignment, Reference, Wiki description explanation, brief detail


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