On the parallel complexity of discrete relaxation in constraint satisfaction networks
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
Improved Exact Algorithms for MAX-SAT
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
Partition-Based Lower Bound for Max-CSP
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Partial Constraint Satisfaction
Over-Constrained Systems
MaxSolver: an efficient exact algorithm for (weighted) maximum satisfiability
Artificial Intelligence
Automated theorem proving: A logical basis (Fundamental studies in computer science)
Automated theorem proving: A logical basis (Fundamental studies in computer science)
In the quest of the best form of local consistency for weighted CSP
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Problem structure in the presence of perturbations
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Local search algorithms for partial MAXSAT
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
New inference rules for Max-SAT
Journal of Artificial Intelligence Research
MINIMAXSAT: an efficient weighted max-SAT solver
Journal of Artificial Intelligence Research
Partial max-SAT solvers with clause learning
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
On inconsistent clause-subsets for Max-SAT solving
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Modelling Max-CSP as partial Max-SAT
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
A preprocessor for Max-SAT solvers
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
Max-SAT formalisms with hard and soft constraints
AI Communications
An empirical study of encodings for group MaxSAT
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
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We present a new generic problem solving approach for over-constrained problems based on Max-SAT. We first define a Boolean clausal form formalism, called soft CNF formulas, that deals with blocks of clauses instead of individual clauses, and that allows one to declare each block either as hard (i.e., must be satisfied by any solution) or soft (i.e., can be violated by some solution). We then present two Max-SAT solvers that find a truth assignment that satisfies all the hard blocks of clauses and the maximum number of soft blocks of clauses. Our solvers are branch and bound algorithms equipped with original lazy data structures, powerful inference techniques, good quality lower bounds, and original variable selection heuristics. Finally, we report an experimental investigation on a representative sample of instances (random 2-SAT, Max-CSP, graph coloring, pigeon hole and quasigroup completion) which provides experimental evidence that our approach is very competitive compared with the state-of-the-art approaches developed in the CSP and SAT communities.