Extending and implementing the stable model semantics
Artificial Intelligence
Counting Models Using Connected Components
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Good Learning and Implicit Model Enumeration
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Classification Algorithms for Codes and Designs (Algorithms and Computation in Mathematics)
Classification Algorithms for Codes and Designs (Algorithms and Computation in Mathematics)
Handbook of Combinatorial Designs, Second Edition (Discrete Mathematics and Its Applications)
Handbook of Combinatorial Designs, Second Edition (Discrete Mathematics and Its Applications)
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications
Solution Enumeration for Projected Boolean Search Problems
CPAIOR '09 Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Using more reasoning to improve #SAT solving
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Towards understanding and harnessing the potential of clause learning
Journal of Artificial Intelligence Research
Counting solutions of integer programs using unrestricted subtree detection
CPAIOR'08 Proceedings of the 5th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
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
Heuristics for fast exact model counting
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
sharpSAT: counting models with advanced component caching and implicit BCP
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
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Many tasks in combinatorial computation admit a natural formulation as instances of the exact cover problem. We observe that the exact cover problem can in turn be compactly translated to the satisfiability (SAT) problem, allowing the basic Davis-Putnam-Logemann-Loveland procedure with no clause learning to linearly simulate backtrack search for exact cover. This SAT-based approach is empirically compared with a widely applied backtrack search algorithm, Knuth's "Dancing Links X" algorithm, on a set of benchmark problems arising in combinatorial enumeration. The experimental results indicate that the current model-counting SAT solvers are in general superior in pruning the search space, but still need to be optimized for running time.