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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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.read more
Citations
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Journal ArticleDOI
Limitations of restricted branching in clause learning
Matti Järvisalo,Tommi Junttila +1 more
TL;DR: This work considers branching heuristics in the context of propositional satisfiability (SAT), where CSPs are expressed as propositional formulas and analyzes the effect of input-restricted branching on clause learning solvers in practice with various structured real-world benchmarks.
Journal ArticleDOI
Engineering constraint solvers for automatic analysis of probabilistic hybrid automata
TL;DR: This article recalls different approaches to the constraint-based, symbolic analysis of hybrid discrete-continuous systems and combines them to a technology able to address hybrid systems exhibiting both non-deterministic and probabilistic behavior akin to infinite-state Markov decision processes.
Journal ArticleDOI
Proof Checking Technology for Satisfiability Modulo Theories
TL;DR: A common proof format for solvers for Satisfiability Modulo Theories (SMT) is proposed, based on the Edinburgh Logical Framework, and LF with Side Conditions (LFSC) extends LF to allow side conditions to be expressed using a simple first-order functional programming language.
Journal ArticleDOI
Resolution Trees with Lemmas: Resolution Refinements that Characterize DLL Algorithms with Clause Learning
TL;DR: In this article, a general form of clause learning, called DLL-Learn, is defined that is equivalent to regular WRTL, and a variable extension method is used to give simulations of resolution by regular WRTI, using a simplified form of proof trace extensions.
Proceedings ArticleDOI
Memoization and DPLL: formula caching proof systems
TL;DR: This work considers extensions of the DPLL approach to satisfiability testing that add some version of memoization, remembering formulas the algorithm has previously shown unsatisfiable, and characterize the strength of various versions in terms of proof systems.
References
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Book
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.
Book
Introduction to Algorithms
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.
Journal ArticleDOI
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.