An optimal k-consistency algorithm
Artificial Intelligence
Characterising tractable constraints
Artificial Intelligence
Synthesizing constraint expressions
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Resolution versus Search: Two Strategies for SAT
Journal of Automated Reasoning
Efficient conflict driven learning in a boolean satisfiability solver
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A Game-Theoretic Approach to Constraint Satisfaction
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
The Quest for Efficient Boolean Satisfiability Solvers
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Propositional Satisfiability and Constraint Programming: A comparative survey
ACM Computing Surveys (CSUR)
A combinatorial characterization of resolution width
Journal of Computer and System Sciences
Compiling finite linear CSP into SAT
Constraints
MINION: A Fast, Scalable, Constraint Solver
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Clause-Learning Algorithms with Many Restarts and Bounded-Width Resolution
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Towards understanding and harnessing the potential of clause learning
Journal of Artificial Intelligence Research
Constraint Satisfaction Problems of Bounded Width
FOCS '09 Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
On the power of clause-learning SAT solvers with restarts
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
ICALP'07 Proceedings of the 34th international conference on Automata, Languages and Programming
Clause-learning algorithms with many restarts and bounded-width resolution
Journal of Artificial Intelligence Research
The order encoding: from tractable CSP to tractable SAT
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
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In this paper we show that the power of using k-consistency techniques in a constraint problem is precisely captured by using a particular inference rule, which we call positive-hyper-resolution, on the direct Boolean encoding of the CSP instance. We also show that current clause-learning SAT-solvers will deduce any positive-hyper-resolvent of a fixed size from a given set of clauses in polynomial expected time. We combine these two results to show that, without being explicitly designed to do so, current clause-learning SAT-solvers efficiently simulate k-consistency techniques, for all values of k. We then give some experimental results to show that this feature allows clause-learning SAT-solvers to efficiently solve certain families of CSP instances which are challenging for conventional CP solvers.