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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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Subsumption-driven clause learning with DPLL+restarts.

TL;DR: It is shown that this approach to solve SAT instances by successive simplifications based on the production of clauses that subsume the initial clauses allows the refutation of pebbling formulae in polynomial time and linear space, as effectively as with a CDCL solver.
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Tuning SAT solvers for LTL Model Checking

TL;DR: Li et al. as discussed by the authors proposed a SAT-based LTL BMC solver, called BSaLTic, which identifies and exploits a new set of relevant (learnt) clauses.

An Experimental Study of Search Strategies and Heuristics in Answer Set Programming.

TL;DR: The results show that, despite the strong link between ASP and SAT, it is not always the case that search strategies, heuristics and/or their combinations that currently dominate in SAT are also bound to dominate in ASP.
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A Probabilistic Approach to Satisfiability of Propositional Logic Formulae.

TL;DR: The proposed BetaWalkSAT algorithm can outperform other uninformed local search approaches for complex boolean satisfiability problems and use probabilistic reasoning for biasing the starting state of the local search algorithm.

A Theory-Based Decision Heuristic for Disjunctive Linear Arithmetic

TL;DR: This work studies the decision problem of Disjunctive Linear Arithmetic over the Reals from the perspective of computational geometry and shows a branching heuristic that is based on approximating T -implications, based on a geometric analysis.
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.
Book

Genetic Algorithms

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.