Explanation Based Learning

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