Satisfiability testing: recent developments and challenge problems

B. Selman
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引用次数: 8

Abstract

Recently, there has been much progress in the area of prepositional reasoning and search. Current techniques can handle problem instances with thousands of variables and up to a million clauses. This has led to new applications in areas such as planning, scheduling, protocol verification, and software testing. Much of the recent progress has resulted from a better understanding of the computational characteristics of the satisfiability problem. In particular, by exploiting connections between combinatorial problems and models from statistical physics, we now have methods that enable a much finer-grained characterization of computational complexity than the standard worst-case complexity measures. These findings provide insights into new algorithmic strategies based on randomization and distributed algorithm portfolios. I will survey the recent progress in this area and I will discuss the current state-of-the-art in propositional reasoning focusing on a series of challenge problems concerning propositional encodings, compilation techniques, approximate reasoning, robustness, and scalability.
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可满足性测试:最近的发展和挑战问题
近年来,介词推理和搜索领域取得了很大的进展。当前的技术可以处理具有数千个变量和多达一百万个子句的问题实例。这导致了诸如计划、调度、协议验证和软件测试等领域的新应用。最近的许多进展是由于对可满足性问题的计算特性有了更好的理解。特别是,通过利用统计物理中的组合问题和模型之间的联系,我们现在有了比标准的最坏情况复杂性度量方法更细粒度的计算复杂性表征方法。这些发现为基于随机化和分布式算法组合的新算法策略提供了见解。我将概述这一领域的最新进展,并将讨论当前命题推理的最新技术,重点关注一系列关于命题编码、编译技术、近似推理、鲁棒性和可扩展性的挑战问题。
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