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Heuristic Planning with SAT: Beyond Uninformed Depth-First Search

Rintanen, Jussi


Planning-specific heuristics for SAT have recently been shown to produce planners that match best earlier ones that use other search methods, including the until now dominant heuristic state-space search. The heuristics are simple and natural, and enforce pure depth-first search with backward chaining in the standard conflict-directed clause learning (CDCL) framework. In this work we consider alternatives to pure depth-first search, and show that carefully chosen randomized search order, which...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Conference paper
Source: Proceedings of the Australasian Joint Conference on Artificial Intelligence (AI 2010)
DOI: 10.1007/978-3-642-17432-2_42


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