2007 · 22 citations · 14 references
Local search algorithms for satisfiability testing are still the best methods for a large number of problems, despite tremendous progresses observed on complete search algorithms over the last few years. However, their intrinsic limit does not allow them to address UNSAT problems. Ten years ago, this question challenged the community without any answer: was it possible to use local search algorithm for UNSAT formulae? We propose here a first approach addressing this issue, that can beat the best resolution-based complete methods. We define the landscape of the search by approximating the number of filtered clauses by resolution proof. Furthermore, we add high-level reasoning mechanism, based on Extended Resolution and Unit Propagation Look-Ahead to make this new and challenging approach possible. Our new algorithm also tends to be the first step on two other challenging problems: obtaining short proofs for UNSAT problems and build a real local-search algorithm for QBF. 1
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A Machine-Oriented Logic Based on the Resolution Principle
John A. Robinson · Journal of the ACM · 1965 · 3.9K citations · Full text
A machine program for theorem-proving
Martin Davis, George Logemann, Donald Loveland · Communications of the ACM · 1962 · 3.1K citations · Full text
Matthew W. Moskewicz, Conor Madigan, Ying Zhao et al. · 2001 · 2.9K citations
Mathematical Programming, Artificial Intelligence, Constraint Solving +14
A Computing Procedure for Quantification Theory
Martin Davis, Hilary Putnam · Journal of the ACM · 1960 · 2.6K citations · Full text
Computational Complexity Theory, Engineering, Constructive Logic +18
A new method for solving hard satisfiability problems
Bart Selman, Hector J. Levesque, David G. M. Mitchell · 1992 · 1.2K citations