Symmetric Explanation Learning: Effective Dynamic Symmetry Handling for SAT

Devriendt, Jo; Bogaerts, Bart; Bruynooghe, Maurice

doi:10.1007/978-3-319-66263-3_6

Cited by 17 publications

(16 citation statements)

References 21 publications

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“…Recent improvements of static symmetry breaking [17] for SAT could be lifted to QBF and applied in combination with recent preprocessing techniques. Also dynamic symmetry breaking during the solving could be beneficial, for example in the form of symmetric explanation learning [24].…”

Section: Construction Of Symmetry Breakersmentioning

confidence: 99%

Symmetries of Quantified Boolean Formulas

Kauers¹,

Seidl²

2018

Theory and Applications of Satisfiability Testing – SAT 2018

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While symmetries are well understood for Boolean formulas and successfully exploited in practical SAT solving, less is known about symmetries in quantified Boolean formulas (QBF). There are some works introducing adaptions of propositional symmetry breaking techniques, with a theory covering only very specific parts of QBF symmetries. We present a general framework that gives a concise characterization of symmetries of QBF. Our framework naturally incorporates the duality of universal and existential symmetries resulting in a general basis for QBF symmetry breaking.Symmetry breaking for QBF has already been studied more than ten years ago [5,6,7], and it can have a dramatic effect on the performance of QBF solvers. As an extreme example, the instances of the KBKF benchmark set [8] are highly symmetric. For some problem sizes n, we applied the two configurations QRes (standard Q-resolution) and LD (long-distance resolution) of the solver DepQBF [9] to this benchmark set. For LD ⋆

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Section: Construction Of Symmetry Breakersmentioning

confidence: 99%

Symmetries of Quantified Boolean Formulas

Kauers¹,

Seidl²

2018

Theory and Applications of Satisfiability Testing – SAT 2018

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“…Symmetry is another characteristic of SAT problem. Jo Devriendt et al [15] present symmetric explanation learning (SEL), in which symmetric clauses are learned only when they are unit or conflicting. 1300 benchmark instances indicate that among GLUCOSE, BREAKID, SEL, SP, SLS, SEL outperforms other four solver configurations and as a dynamic symmetry handling technique, SEL is the first one competitive with static symmetry breaking which is known to the most effective way to handle symmetry.…”

Section: A Related Workmentioning

confidence: 99%

An Efficient Method to Transform a SAT problem to a Mixed Integer Linear Programming Problem

Guo

Wang²,

et al. 2018

2018 IEEE 4th International Conference on Computer and Communications (ICCC)

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In computational complexity theory, a decision problem is NP-complete when it is both in NP and NP-hard. Although a solution to a NP-complete can be verified quickly, there is no known algorithm to solve it in polynomial time. There exists a method to reduce a SAT (Satifiability) problem to Subset Sum Problem (SSP) in the literature, however, it can only be applied to small or medium size problems. Our study is to find an efficient method to transform a SAT problem to a mixed integer linear programming problem in larger size. Observing the feature of variable-clauses constraints in SAT, we apply linear inequality model (LIM) to the problem and propose a method called LIMSAT. The new method can work efficiently for very large size problem with thousands of variables and clauses in SAT tested using up-to-date benchmarks.

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“…They intervene directly during the search exploration. It concerns, to mention but a few, the injection of symmetric versions of learned clauses [7,21], particular classes of symmetries [20], or speeding up the search by inferring symmetric facts [9]. These approaches succeeded in treating particular and hand crafted problems but, to the best of our knowledge, none of them is competitive face to the static symmetry breaking methods.…”

Section: Introductionmentioning

confidence: 99%

CDCLSym: Introducing Effective Symmetry Breaking in SAT Solving

Metin¹,

Baarir

Colange

et al. 2018

Lecture Notes in Computer Science

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Abstract. SAT solvers are now widely used to solve a large variety of problems, including formal verification of systems. SAT problems derived from such applications often exhibit symmetry properties that could be exploited to speed up their solving. Static symmetry breaking is so far the most popular approach to take advantage of symmetries. It relies on a symmetry preprocessor which augments the initial problem with constraints that force the solver to consider only a few configurations among the many symmetric ones. This paper presents a new way to handle symmetries, that avoid the main problem of the current static approaches: the prohibitive cost of the preprocessing phase. Our proposal has been implemented in MiniSym. Extensive experiments on the benchmarks of last six SAT competitions show that our approach is competitive with the best state-of-the-art static symmetry breaking solutions.

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Symmetric Explanation Learning: Effective Dynamic Symmetry Handling for SAT

Cited by 17 publications

References 21 publications

Symmetries of Quantified Boolean Formulas

Symmetries of Quantified Boolean Formulas

An Efficient Method to Transform a SAT problem to a Mixed Integer Linear Programming Problem

CDCLSym: Introducing Effective Symmetry Breaking in SAT Solving

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