On the power of clause-learning SAT solvers as resolution engines

Author:

Pipatsrisawat Knot,Darwiche Adnan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference30 articles.

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2. G. Audemard, L. Bordeaux, Y. Hamadi, S. Jabbour, L. Sais, A generalized framework for conflict analysis, in: Proceedings of 11th International Conference on Theory and Applications of Satisfiability Testing (SAT'08), 2008, pp. 21–27.

3. G. Audemard, L. Simon, Predicting learnt clauses quality in modern SAT solver, in: Proceedings of 21st International Joint Conference on Artificial Intelligence (IJCAI'09), July 2009, pp. 399–404.

4. R.J.J. Bayardo, R.C. Schrag, Using CSP look-back techniques to solve real-world SAT instances, in: Proceedings of 14th National Conference on Artificial Intelligence (AAAI-97), 1997, pp. 203–208.

5. Towards understanding and harnessing the potential of clause learning;Beame;Journal of Artificial Intelligence Research,2004

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