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Monte-Carlo Tree Search for the Maximum Satisfiability Problem

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Book cover Principles and Practice of Constraint Programming (CP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9892))

Abstract

Incomplete algorithms for the Maximum Satisfiability (MaxSAT) problem use a hill climbing approach in tandem with various mechanisms that prevent search stagnation. These solvers’ conflicting goals of maintaining search mobility while discovering high quality solutions constitute an exploration-exploitation dilemma, a problem which has been tackled with great success in recent years using Monte-Carlo Tree Search (MCTS) methods. We apply MCTS to the domain of MaxSAT using various stochastic local search (SLS) algorithms for leaf node value estimation, thus offering a novel hybrid alternative to established complete and incomplete solution techniques. Our algorithm outperforms baseline SLS algorithms like Walksat and Novelty on most problem instances from the 2015 MaxSAT Evaluation. It also outdoes CCLS, a state-of-the-art incomplete MaxSAT solver, on a number of challenging industrial instances from the 2015 MaxSAT Evaluation.

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Notes

  1. 1.

    http://www.maxsat.udl.cat/15/, accessed on Feb. 21, 2016.

  2. 2.

    http://www.maxsat.udl.cat/15/results-incomplete/index.html, retrieved on Feb. 21, 2016.

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Acknowledgements

We are grateful to Shaowei Cai and his collaborators for sharing their implementation of the CCLS algorithm with us. We would also like to thank the anonymous reviewers for their useful comments and feedback.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, Davidson College, Davidson, NC, 28035, USA

    Jack Goffinet & Raghuram Ramanujan

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  1. Jack Goffinet
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  2. Raghuram Ramanujan
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Correspondence to Raghuram Ramanujan .

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Editors and Affiliations

  1. University of Nice Sophia Antipolis , Sophia Antipolis, France

    Michel Rueher

A Appendix: The Uctmaxsat Algorithm

A Appendix: The Uctmaxsat Algorithm

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Goffinet, J., Ramanujan, R. (2016). Monte-Carlo Tree Search for the Maximum Satisfiability Problem. In: Rueher, M. (eds) Principles and Practice of Constraint Programming. CP 2016. Lecture Notes in Computer Science(), vol 9892. Springer, Cham. https://doi.org/10.1007/978-3-319-44953-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-44953-1_17

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