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Complexity and structural heuristics for propositional and quantified satisfiability.

机译:命题和量化可满足性的复杂性和结构启发法。

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摘要

Decision procedures for various logics are used as general-purpose solvers in computer science. A particularly popular choice is propositional logic, which is simultaneously powerful enough to model problems in many application domains, including formal verification and planning, while at the same time simple enough to be efficiently solved for many practical cases. Similarly, there are also recent interests in using QBF, an extension of propositional logic, as a modeling language to be used in a similar fashion. The hope is that QBF, being a more powerful language, can compactly encode, and in turn, be used to solve, a larger range of applications. Still, propositional logic and QBF are respectively complete for the complexity classes NP and PSPACE, thus, both can be theoretically considered intractable. A popular hypothesis is that real-world problems contain underlying structure that can be exploited by the decision procedures. In this dissertation, we study the impact of structural constraints (in the form of bounded width) and heuristics on the performance of propositional and QBF decision procedures.;The results presented in this dissertation can be seen as a contrast on how bounded-width impacts propositional and quantified problems differently. Starting with a size bound on BDDs under bounded width, we proceed to compare symbolic decision procedures against the standard DPLL search-based approach for propositional logic, as well as compare different width-based heuristics for the symbolic approaches. In general, symbolic approaches for propositional satisfiability are only competitive for a small range of problems, and the theoretical tractability for the bounded-width case rarely applies in practice. However, the picture is very different for quantified satisfiability. To that end, we start with a series of "intractability in tractability" results which shows that although the complexity of QBF with constant width and alternation is tractable, there is an inherent non-elementary blowup in the width and alternation depth such that a width-bound that is slightly above constant leads to intractability. To contrast the theoretical intractability, we apply structural heuristics to a symbolic decision procedure of QBF and show that symbolic approaches complement search-based approaches quite well for QBF.
机译:各种逻辑的决策过程在计算机科学中用作通用求解器。命题逻辑是一个特别受欢迎的选择,命题逻辑同时强大到足以在许多应用领域(包括形式验证和计划)中对问题进行建模,同时又足够简单,可以针对许多实际情况进行有效解决。同样,最近也有兴趣使用QBF(命题逻辑的扩展)作为要以类似方式使用的建模语言。希望QBF是一种功能更强大的语言,它可以进行紧凑的编码,然后再用于解决更大范围的应用程序。尽管如此,命题逻辑和QBF对于复杂度等级NP和PSPACE分别是完整的,因此,从理论上讲,两者都是难以解决的。一个普遍的假设是,现实世界中的问题包含决策程序可以利用的潜在结构。本文研究了结构约束(以有界宽度的形式)和启发式方法对命题和QBF决策程序的性能的影响。本文所提出的结果可以看作是有界宽度影响的对比。命题和量化问题有所不同。从边界宽度以下的BDD的大小开始,我们将比较符号决策过程与用于命题逻辑的标准DPLL基于搜索的方法,并比较符号方法的不同基于宽度的启发式方法。通常,命题可满足性的象征性方法仅对一小部分问题具有竞争力,而有界案例的理论易处理性在实践中很少应用。但是,图片在量化的可满足性方面大不相同。为此,我们从一系列的“难处理性”入手,结果表明,尽管恒定宽度和交替的QBF的复杂度是易处理的,但宽度和交替深度存在固有的非基本膨胀,使得宽度略高于常数的绑定会导致难处理性。为了对比理论上的难点,我们将结构启发式方法应用于QBF的符号决策过程,并表明符号方法对于QBF很好地补充了基于搜索的方法。

著录项

  • 作者

    Pan, Guoqiang.;

  • 作者单位

    Rice University.;

  • 授予单位 Rice University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 131 p.
  • 总页数 131
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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