Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
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Artificial Intelligence
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AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
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Artificial Intelligence
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SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
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Programming and Computing Software
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IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
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Planning as satisfiability: Heuristics
Artificial Intelligence
Revisiting regression in planning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Generic SAT solvers have been very successful in solving hard combinatorial problems in various application areas, including AI planning. There is potential for improved performance by making the SAT solving process more application-specific. In this paper we propose a variable selection strategy for AI planning. The strategy is based on generic principles about properties of plans, and its performance with standard planning benchmarks often substantially improves on generic variable selection heuristics used in SAT solving, such as the VSIDS strategy. These improvements lift the efficiency of SAT based planning to the same level as best planners that use other search methods.