Incorporating redundant learned rules: a preliminary formal analysis of EBL

Authors:
Russell Greiner;Joseph Likuski
Affiliations:
Department of Computer Science, University of Toronto, Toronto, Ontario;Department of Computer Science, University of Toronto, Toronto, Ontario
Venue:
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Year:
1989

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Abstract

"Explanation-based learning" -- i.e., incorporating new redundant rules suggested by earlier problem solving experiences -- is an attempt to speed up problem solving. Unfortunately, the resulting systems are not always more efficient on subsequent problems. This paper describes, analytically, whether these new rules should be added, and if so, where they should appear in the overall derivation strategy. While this task is intractable in general, we present several interesting special cases which can be solved in time (essentially) linear in the number of rules in the system.