Efficient conflict driven learning in a boolean satisfiability solver
Lintao Zhang,Conor F. Madigan,Matthew H. Moskewicz,Sharad Malik +3 more
- pp 279-285
Reads0
Chats0
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
More filters
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.
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
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
More filters
Book
Planning and Control
Thomas Dean,Michael P. Wellman +1 more
TL;DR: This book is useful to researchers in artificial intelligence and control theory, and others concerned with the design of complex applications in robotics, automated manufacturing, and time-critical decision support.
Journal ArticleDOI
Applying tabu search to the job-shop scheduling problem
Mauro Dell'Amico,Marco Trubian +1 more
TL;DR: This paper applies the tabu-search technique to the job-shop scheduling problem, a notoriously difficult problem in combinatorial optimization and shows that the implementation of this method dominates both a previous approach with tabu search and the other heuristics based on iterative improvements.
Journal ArticleDOI
The use of design descriptions in automated diagnosis
TL;DR: Dart differs from previous approaches to diagnosis taken in the design-automation community in that it is more general and in many cases more efficient, and allows it to be applied to a wide class of devices ranging from digital logic to nuclear reactors.
Book ChapterDOI
SATO: An Efficient Propositional Prover
TL;DR: Two techniques that are found eeective to improve SATO performance are discussed, one is about splitting rules; the other is about connict analysis.