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
Citations
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Book ChapterDOI
An Extensible SAT-solver
Niklas Een,Niklas Sörensson +1 more
TL;DR: This article presents a small, complete, and efficient SAT-solver in the style of conflict-driven learning, as exemplified by Chaff, and includes among other things a mechanism for adding arbitrary boolean constraints.
Book
Handbook of Constraint Programming
TL;DR: Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.
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SATzilla: portfolio-based algorithm selection for SAT
TL;DR: SATzilla is described, an automated approach for constructing per-instance algorithm portfolios for SAT that use so-called empirical hardness models to choose among their constituent solvers and is improved by integrating local search solvers as candidate solvers, by predicting performance score instead of runtime, and by using hierarchical hardness models that take into account different types of SAT instances.
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Solving SAT and SAT Modulo Theories: From an abstract Davis--Putnam--Logemann--Loveland procedure to DPLL(T)
TL;DR: Extensive experimental evidence shows that DPLL(T) systems can significantly outperform the other state-of-the-art tools, frequently even in orders of magnitude, and have better scaling properties.
Book ChapterDOI
Satisfiability Modulo Theories
Clark Barrett,Cesare Tinelli +1 more
TL;DR: The architecture of a lazy SMT solver is discussed, examples of theory solvers are given, how to combine such solvers modularly is shown, and several extensions of the lazy approach are mentioned.
References
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Proceedings Article
The hazards of fancy backtracking
TL;DR: It is shown that for some problems it can be counterproductive to return to the source of a difficulty without erasing the intermediate work, and that such "intelligence" can cause an exponential increase in the size of the ultimate search space.
Proceedings Article
Exploiting a common property resource under a fairness constraint: a case study
TL;DR: This paper investigates a decision problem for which the common property resource is an earth observation satellite and proposes three ways for solving this share problem, which gives priority to fairness, the second one to efficiency, and the third one computes a set of compromises.
Journal Article
Why adding more constraints makes a problem easier for hill-climbing algorithms : Analyzing landscapes of CSPs
TL;DR: This paper exhaustively analyzes the state-space landscape of CSPs and shows that by adding more constraints, while the number of solutions decreases, thenumber of local-minima also decreases, thus theNumber of states that are reachable to solutions increases.
Journal ArticleDOI
An Overview of Backtrack Search Satisfiability Algorithms
Inês Lynce,Joao Marques-Silva +1 more
TL;DR: An overview of backtrack search SAT algorithms is provided, describing and illustrating a number of techniques that have been empirically shown to be highly effective in pruning the amount of search on significant and representative classes of problem instances.
Journal ArticleDOI
Negative Effects of Modeling Techniques on Search Performance
TL;DR: It is found that adding symmetry breaking constraints to a model impairs local search performance, in terms of both execution time and search steps, and implied constraints can impair backtrack search performance.