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arXiv · 1301.6708

Mini-Bucket Heuristics for Improved Search

Kalev Kask·Rina Dechter
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Abstract

The paper is a second in a series of two papers evaluating the power of a new scheme that generates search heuristics mechanically. The heuristics are extracted from an approximation scheme called mini-bucket elimination that was recently introduced. The first paper introduced the idea and evaluated it within Branch-and-Bound search. In the current paper the idea is further extended and evaluated within Best-First search. The resulting algorithms are compared on coding and medical diagnosis problems, using varying strength of the mini-bucket heuristics. Our results demonstrate an effective search scheme that permits controlled tradeoff between preprocessing (for heuristic generation) and search. Best-first search is shown to outperform Branch-and-Bound, when supplied with good heuristics, and sufficient memory space.

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Kalev Kask, Rina Dechter. 2013-01-23. Mini-Bucket Heuristics for Improved Search. https://arxiv.org/abs/1301.6708

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