Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
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Nonserial Dynamic Programming
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UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Branch and bound with mini-bucket heuristics
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
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UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
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UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Mini-buckets: A general scheme for bounded inference
Journal of the ACM (JACM)
Conflict-directed A* and its role in model-based embedded systems
Discrete Applied Mathematics
Semiring induced valuation algebras: Exact and approximate local computation algorithms
Artificial Intelligence
Integrated plan tracking and prognosis for autonomous production processes
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
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CPAIOR'08 Proceedings of the 5th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
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KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Automated plan assessment in cognitive manufacturing
Advanced Engineering Informatics
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International Journal of Approximate Reasoning
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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 sup plied with good heuristics, and sufficient memory space.