Extract general rules from examples

**EXPLANATION BASED LEARNING**

â€¢ Extract
general rules from examples

â€¢ Basic
idea

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

â€“ In
parallel, construct a generalized proof with variabilized goal.

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

â€“ Drop
any conditions that are always true regardless of value of variables in the
goal.

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

â€¢
Efficiency, Operationality, Generality

â€“ Too
many rules slows down reasoning

â€“ Rules
should provide speed increase by eliminating dead-ends and shortening the

proof

â€“ As
general as possible to cover the most cases

â€¢ Tradeoffs,
how to maximize the efficiency of the knowledge base?

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

â€¢
Efficiency, Operationality, Generality

â€“ Too
many rules slows down reasoning

â€“ Rules
should provide speed increase by eliminating dead-ends and shortening the proof

â€“ As
general as possible to cover the most cases

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Artificial Intelligence : Explanation Based Learning |

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