A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
On the complexity of choosing the branching literal in DPLL
Artificial Intelligence
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
The Impact of Branching Heuristics in Propositional Satisfiability Algorithms
EPIA '99 Proceedings of the 9th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
The Quest for Efficient Boolean Satisfiability Solvers
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Conflict Analysis in Search Algorithms for Satisfiability
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
BerkMin: A Fast and Robust Sat-Solver
Proceedings of the conference on Design, automation and test in Europe
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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The paper is concerned with the computational evaluation and comparison of a new family of conflict-based branching heuristics for evolved DPLL Satisfiability solvers. Such a family of heuristics is based on the use of new scores updating criteria developed in order to overcome some of the typical unpleasant behaviors of DPLL search techniques. In particular, a score is associated with each literal. Whenever a conflict occurs, some scores are incremented with different values, depending on the character of the conflict. The branching variable is then selected by using the maximum among those scores. Several variants of this have been introduced into a state-of-the-art implementation of a DPLL SAT solver, obtaining several versions of the solver having quite different behavior. Experiments on many benchmark series, both satisfiable and unsatisfiable, demonstrate advantages of the proposed heuristics.