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On the Run-time Behaviour of Stochastic Local Search Algorithms for SAT (1999)
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@MISC{Hoos99onthe,
author = {Holger H. Hoos},
title = {On the Run-time Behaviour of Stochastic Local Search Algorithms for SAT},
year = {1999}
}
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Abstract
Stochastic local search (SLS) algorithms for the propositional satisfiability problem (SAT) have been successfully applied to solve suitably encoded search problems from various domains. One drawback of these algorithms is that they are usually incomplete. We refine the notion of incompleteness for stochastic decision algorithms by introducing the notion of "probabilistic asymptotic completeness" (PAC) and prove for a number of well-known SLS algorithms whether or not they have this property. We also give evidence for the practical impact of the PAC property and show how to achieve the PAC property and significantly improved performance in practice for some of the most powerful SLS algorithms for SAT, using a simple and general technique called "random walk extension".
Keyphrases
run-time behaviour stochastic local search algorithm pac property well-known sl algorithm powerful sl algorithm various domain general technique stochastic decision algorithm search problem practical impact stochastic local search random walk extension probabilistic asymptotic completeness propositional satisfiability problem
