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Open AccessProceedings ArticleDOI

Efficient conflict driven learning in a boolean satisfiability solver

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TLDR
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.

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Book ChapterDOI

An Extensible SAT-solver

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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

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

Valued constraint satisfaction problems: hard and easy problems

TL;DR: A simple algebraic framework is considered, related to Partial Constraint Satisfaction, which subsumes most of these proposals and is used to characterize existing proposals in terms of rationality and computational complexity.
Proceedings Article

Using CSP look-back techniques to solve real-world SAT instances

TL;DR: The results show that incorporating CSP look-back techniques renders easy many problems which otherwise are beyond DP's reach, and recommend that such techniques be included as options in implementations of DP, just as they are in systematic algorithms for the more general constraint satisfaction problem.

Local Search Strategies for Satisfiability Testing

TL;DR: The power of local search for satissability testing can be further enhanced by employing a new strategy, called mixed random walk, for escaping from local minima, which allows us to handle formulas that are substantially larger than those that can be solved with basic local search.
Proceedings Article

Boosting combinatorial search through randomization

TL;DR: This work presents a general method for introducing controlled randomization into complete search algorithms and demonstrates speedups of several orders of magnitude for state-of-the-art complete search procedures running on hard, real-world problems.
Journal ArticleDOI

Hybrid algorithms for the constraint satisfaction problem

TL;DR: This paper presents an approach that allows base algorithms to be combined, giving us new hybrids, and it is shown that FC‐CBJ is by far the best of the algorithms examined.