Stratified case-based reasoning: reusing hierarchical problem solving episodes

Authors:
L. Karl Branting;David W. Aha
Affiliations:
Department of Computer Science, University of Wyoming, Laramie, WY;Navy Center for Applied Research in AI, Naval Research Laboratory, Washington, DC
Venue:
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Year:
1995

Citing 10
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Abstract

Stratified case-based reasoning is a technique in which abstract solutions produced during hierarchical problem solving are used to assist case-based retrieval, matching, and adaptation. We describe the motivation for the integration of case-based reasoning with hierarchical problem solving, exemplify its benefits, detail a set of algorithms that implement our approach, and present their comparative empirical evaluation on a path planning task. Our results show that stratified case-based reasoning significantly decreases the computational expense required to retrieve, match, and adapt cases, leading to performance superior both to simple case-based reasoning and to hierarchical problem solving ab initio.