Efficient conflict driven learning in a boolean satisfiability solver
Lintao Zhang,Conor F. Madigan,Matthew H. Moskewicz,Sharad Malik +3 more
- pp 279-285
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This paper generalizes various conflict driven learning strategies in terms of different partitioning schemes of the implication graph to re-examine the learning techniques used in various SAT solvers and propose an array of new learning schemes.Abstract:
One of the most important features of current state-of-the-art SAT solvers is the use of conflict based backtracking and learning techniques. In this paper, we generalize various conflict driven learning strategies in terms of different partitioning schemes of the implication graph. We re-examine the learning techniques used in various SAT solvers and propose an array of new learning schemes. Extensive experiments with real world examples show that the best performing new learning scheme has at least a 2/spl times/ speedup compared with learning schemes employed in state-of-the-art SAT solvers.read more
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Clause-learning algorithms with many restarts and bounded-width resolution
TL;DR: It is proved that, although the solver is not explicitly designed for it, with high probability it ends up behaving as width-k resolution after no more than O(n2k+2) conflicts and restarts, where n is the number of variables.
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Conflict-driven disjunctive answer set solving
Christian Drescher,Martin Gebser,Torsten Grote,Benjamin Kaufmann,Arne König,Max Ostrowski,Torsten Schaub +6 more
TL;DR: A uniform approach to computing answer sets of disjunctive logic programs based on state-of-the-art Boolean constraint solving techniques, featuring backjumping and conflict-driven learning using the First-UIP scheme as well as sophisticated unfounded set checking.
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Heuristics for fast exact model counting
Tian Sang,Paul Beame,Henry Kautz +2 more
TL;DR: The result of this work is a highly-tuned version of Cachet, the first (and currently, only) system able to exactly determine the marginal probabilities of variables in random 3-SAT formulas with 150+ variables.
Proceedings ArticleDOI
Program synthesis using conflict-driven learning
TL;DR: Neo as mentioned in this paper proposes a new conflict-driven program synthesis technique that is capable of learning from past mistakes by identifying the root cause of the conflict and learning new lemmas that can prevent similar mistakes in the future.
References
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Computers and Intractability: A Guide to the Theory of NP-Completeness
TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
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TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
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Tabu Search—Part II
TL;DR: The elements of staged search and structured move sets are characterized, which bear on the issue of finiteness, and new dynamic strategies for managing tabu lists are introduced, allowing fuller exploitation of underlying evaluation functions.