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Abstract

Local search is widely applied to satisfiable SAT problems, and on some classes outperforms backtrack search. An intriguing challenge posed by Selman, Kautz and McAllester in 1997 is to use it instead to prove unsatisfiability. We investigate two distinct approaches. Firstly we apply standard local search to a reformulation of the problem, such that a solution to the reformulation corresponds to a refutation of the original problem. Secondly we design a greedy randomised resolution algorithm that will eventually discover proofs of any size while using bounded memory. We show experimentally that both approaches can refute some problems more quickly than backtrack search.

Keywords

Local Search Constraint Program Local Search Algorithm General Resolution Empty Clause 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Steven Prestwich
    • 1
  • Inês Lynce
    • 2
  1. 1.Cork Constraint Computation Centre, Department of Computer ScienceUniversity CollegeCorkIreland
  2. 2.IST/INESC-IDTechnical University of LisbonPortugal

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