Improving Graphplan's search with EBL & DDB techniques

Authors:
Subbarao Kambhampati
Affiliations:
Department of Computer Science and Engineering, Arizona State University, Tempe, AZ
Venue:
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Year:
1999

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Abstract

I highlight some inefficiencies of Graphplan's backward search algorithm, and describe how these can be eliminated by adding explanation-based learning and dependency-directed backtracking capabilities to Graphplan. I will then demonstrate the effectiveness of these augmentations by describing results of empirical studies that show dramatic improvements in run-time (w 100× speedups) as well as solvability-horizons on benchmark problems across seven different domains.