SAT vs. search for qualitative temporal reasoning
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Huang, Jinbo
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IOS Press BV
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Abstract
Empirical data from recent work has indicated that SAT-based solvers can outperform native search-based solvers on certain classes of problems in qualitative temporal reasoning, particularly over the Interval Algebra (IA). The present work shows that, for reasoning with IA, SAT strictly dominates search in theoretical power: (1) We present a SAT encoding of IA that simulates the use of tractable subsets in native solvers. (2) We show that the refutation of any inconsistent IA network can always be done by SAT (via our new encoding) as efficiently as by native search. (3) We exhibit a class of IA networks that provably require exponential time to refute by native search, but can be refuted by SAT in polynomial time.
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ECAI 2012 - 20th European Conference on Artificial Intelligence, 27-31 August 2012, Montpellier, France - Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstration
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