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Variable Dependency in Local Search: Prevention Is Better Than Cure

  • Conference paper
Theory and Applications of Satisfiability Testing – SAT 2007 (SAT 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4501))

Abstract

Local search achieves good results on a variety of SAT problems and often scales up better than backtrack search. But despite recent advances in local search heuristics it has failed to solve some structured problems, while backtrack search has advanced greatly on such problems. We conjecture that current modelling practices are unintentionally biased in favour of solution by backtrack search. To test this conjecture we remodel two problems whose large instances have long resisted solution by local search: parity learning and Towers of Hanoi as STRIPS planning. By reducing variable dependencies and using other techniques we boost local search performance by several orders of magnitude in both cases, and we can now solve 32-bit and 6-disk instances for the first time using a standard SAT local search algorithm.

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Authors and Affiliations

  1. Cork Constraint Computation Centre, Department of Computer Science, University College, Cork, Ireland

    Steven Prestwich

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  1. Steven Prestwich
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João Marques-Silva Karem A. Sakallah

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Prestwich, S. (2007). Variable Dependency in Local Search: Prevention Is Better Than Cure. In: Marques-Silva, J., Sakallah, K.A. (eds) Theory and Applications of Satisfiability Testing – SAT 2007. SAT 2007. Lecture Notes in Computer Science, vol 4501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72788-0_14

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  • DOI: https://doi.org/10.1007/978-3-540-72788-0_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72787-3

  • Online ISBN: 978-3-540-72788-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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