首页> 外文会议>Australian Joint Conference on Artificial Intelligence; 20071202-06; Gold Coast(AU) >Modeling and Solving Semiring Constraint Satisfaction Problems by Transformation to Weighted Semiring Max-SAT
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Modeling and Solving Semiring Constraint Satisfaction Problems by Transformation to Weighted Semiring Max-SAT

机译:通过转换为加权半环Max-SAT建模和解决半环约束满足问题

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We present a variant of the Weighted Maximum Satisfiability Problem (Weighted Max-SAT), which is a modeling of the Semiring Constraint Satisfaction framework. We show how to encode a Semiring Constraint Satisfaction Problem (SCSP) into an instance of a propositional Weighted Max-SAT, and call the encoding Weighted Semiring Max-SAT (WS-Max-SAT). The clauses in our encoding are highly structured and we exploit this feature to develop two algorithms for solving WS-Max-SAT: an incomplete algorithm based on the well-known GSAT algorithm for Max-SAT, and a branch-and-bound algorithm which is complete. Our preliminary experiments show that the translation of SCSP into WS-Max-SAT is feasible, and that our branch-and-bound algorithm performs surprisingly well. We aim in future to combine the natural flexible representation of the SCSP framework with the inherent efficiencies of SAT solvers by adjusting existing SAT solvers to solve WS-Max-SAT.
机译:我们提出了加权最大满意度问题(Weighted Max-SAT)的变体,它是Semiring约束满意度框架的模型。我们展示了如何将Semiring约束满意问题(SCSP)编码为命题加权Max-SAT的实例,并称为编码加权Semiring Max-SAT(WS-Max-SAT)。我们的编码中的子句结构高度结构化,我们利用此功能开发了两种解决WS-Max-SAT的算法:一种基于著名的Max-SAT GSAT算法的不完全算法,以及一种分支定界算法已完成。我们的初步实验表明,将SCSP转换为WS-Max-SAT是可行的,并且我们的分支定界算法的性能出奇地好。我们未来的目标是通过调整现有的SAT解算器来解决WS-Max-SAT,将SCSP框架的自然灵活表示与SAT解算器的固有效率相结合。

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