Size-Space Tradeoffs for Resolution

IF 1.6 3区计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS

SIAM Journal on Computing Pub Date : 2009-02-01 DOI:10.1137/080723880

Eli Ben-Sasson

引用次数: 10

Abstract

We investigate tradeoffs of various basic complexity measures such as size, space, and width. We show examples of formulas that have optimal proofs with respect to any one of these parameters, but optimizing one parameter must cost an increase in the other. These results have implications to the efficiency (or rather, inefficiency) of some commonly used SAT solving heuristics. Our proof relies on a novel connection of the variable space of a proof to the black-white pebbling measure of an underlying graph.

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分辨率的大小空间权衡

我们研究了各种基本复杂性度量(如大小、空间和宽度)的权衡。我们给出了对这些参数中的任何一个都有最优证明的公式示例，但是优化一个参数必须以增加另一个参数为代价。这些结果暗示了一些常用的SAT求解启发式的效率(或者更确切地说，效率低下)。我们的证明依赖于证明的变量空间与底层图的黑白卵石测度之间的一种新的联系。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

SIAM Journal on Computing 工程技术-计算机：理论方法

CiteScore

4.60

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The SIAM Journal on Computing aims to provide coverage of the most significant work going on in the mathematical and formal aspects of computer science and nonnumerical computing. Submissions must be clearly written and make a significant technical contribution. Topics include but are not limited to analysis and design of algorithms, algorithmic game theory, data structures, computational complexity, computational algebra, computational aspects of combinatorics and graph theory, computational biology, computational geometry, computational robotics, the mathematical aspects of programming languages, artificial intelligence, computational learning, databases, information retrieval, cryptography, networks, distributed computing, parallel algorithms, and computer architecture.