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Summary: Old Resolution Meets Modern SLS
Anbulagan1
, Duc Nghia Pham2
, John Slaney1,3
, Abdul Sattar2
1
Logic and Computation Program, National ICT Australia Ltd., Canberra, Australia
2
IIIS, Griffith University, Brisbane, Australia
3
Computer Sciences Laboratory, Australian National University, Canberra, Australia
{anbulagan, john.slaney}@nicta.com.au, {d.n.pham, a.sattar}@griffith.edu.au
Abstract
Recent work on Stochastic Local Search (SLS) for the SAT
and CSP domains has shown the importance of a dynamic
(non-markovian) strategy for weighting clauses in order to es-
cape from local minima. In this paper, we improve the perfor-
mance of two best contemprorary clause weighting solvers,
PAWS and SAPS, by integrating a propositional resolution
procedure. We also extend the work to AdaptNovelty+
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