Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
New inference rules for Max-SAT
Journal of Artificial Intelligence Research
Integrating systematic and local search paradigms: a new strategy for MaxSAT
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Scaling and probabilistic smoothing: dynamic local search for unweighted MAX-SAT
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
Combining adaptive noise and look-ahead in local search for SAT
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Towards more effective unsatisfiability-based maximum satisfiability algorithms
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
UBCSAT: an implementation and experimentation environment for SLS algorithms for SAT and MAX-SAT
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
Using learnt clauses in MAXSAT
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
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We propose a new incomplete algorithm for the Maximum Satisfiability (MaxSAT) problem on unweighted Boolean formulas, focused specifically on instances for which proving unsatisfiability is already computationally difficult. For such instances, our approach is often able to identify a small number of what we call "bottleneck" constraints, in time comparable to the time it takes to prove unsatisfiability. These bottleneck constraints can have useful semantic content. Our algorithm uses a relaxation of the standard backtrack search for satisfiability testing (SAT) as a guiding heuristic, followed by a low-noise local search when needed. This allows us to heuristically exploit the power of unit propagation and clause learning. On a test suite consisting of all unsatisfiable industrial instances from SAT Race 2008, our solver, RelaxedMinisat , is the only (MaxSAT) solver capable of identifying a single bottleneck constraint in all but one instance.