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Breaking Symmetries in SAT Matrix Models

机译:在SAT Matrix模型中打破对称性

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摘要

Symmetry occurs naturally in many computational problems. The use of symmetry breaking techniques for solving search problems reduces the search space and therefore is expected to reduce the search time. Recent advances in breaking symmetries in SAT models are mainly focused on the identification of permutable variables via graph automorphism. These symmetries are denoted as instance-dependent, and although shown to be effective for different problem instances, the advantages of their generalised use in SAT are far from clear. Indeed, in many cases symmetry breaking predicates can introduce significant computational overhead, rendering ineffective the use of symmetry breaking. In contrast, in other domains, symmetry breaking is usually achieved by identifying instance-independent symmetries, often with promising experimental results. This paper studies the use of instance-independent symmetry breaking predicates in SAT. A concrete application is considered, and techniques for symmetry breaking in matrix models from CP are used. Our results indicate that instance-independent symmetry breaking predicates for matrix models can be significantly more effective than instance-dependent symmetry breaking predicates.
机译:对称性在许多计算问题中自然发生。用于解决搜索问题的对称性断开技术减少了搜索空间,因此预计将减少搜索时间。最近在SAT模型中打破对称性的进展主要集中在通过图形自动形态识别可弥补的变量。这些对称性被称为实例依赖性,虽然显示对不同的问题实例有效,但在SAT中的广义使用的优势远非清晰。实际上,在许多情况下,对称性破坏谓词可以引入显着的计算开销,渲染无效地使用对称性断裂。相反,在其他结构域中,通常通过识别与实例 - 独立的对称性来实现对称性破裂,通常具有有前途的实验结果。本文研究了SAT中使用实例独立的对称性断裂谓词。考虑了具体应用,使用了从CP矩阵模型中分解的对称性施用的技术。我们的结果表明,与实例相关的对称性的对称性谓词,矩阵模型的实例与对称性的对称性谓词可以明显更有效。

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