SAT 后门:深度胜于大小

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Jan Dreier , Sebastian Ordyniak , Stefan Szeider
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引用次数: 0

摘要

数十年来,人们一直在努力确定可在多项式时间内确定其满足性的 CNF 公式类别。经典成果是 Horn 公式(Aspvall、Plass 和 Tarjan,1979 年)和 Krom(即 2CNF)公式(Dowling 和 Gallier,1984 年)的线性时间可操作性。Williams、Gomes 和 Selman(2003 年)引入的后门逐渐将这一易处理的类别扩展到与该类公式有一定距离的所有公式。后门大小提供了一个自然但相当粗糙的公式与可扩展类之间的距离度量。后门深度由 Mählmann、Siebertz 和 Vigny(2021 年)提出,是一种更精细的距离度量,它允许并行使用不同的后门变量。我们提出了 FPT 近似算法来计算 Horn 和 Krom 类的后门深度。这就产生了一种线性时间算法,用于判定这些类中后门深度有界的公式的可满足性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SAT backdoors: Depth beats size

For several decades, much effort has been put into identifying classes of CNF formulas whose satisfiability can be decided in polynomial time. Classic results are the linear-time tractability of Horn formulas (Aspvall, Plass, and Tarjan, 1979) and Krom (i.e., 2CNF) formulas (Dowling and Gallier, 1984). Backdoors, introduced by Williams, Gomes and Selman (2003), gradually extend such a tractable class to all formulas of bounded distance to the class. Backdoor size provides a natural but rather crude distance measure between a formula and a tractable class. Backdoor depth, introduced by Mählmann, Siebertz, and Vigny (2021), is a more refined distance measure, which admits the utilization of different backdoor variables in parallel. We propose FPT approximation algorithms to compute backdoor depth into the classes Horn and Krom. This leads to a linear-time algorithm for deciding the satisfiability of formulas of bounded backdoor depth into these classes.

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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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