更快地实现开关列表表示的 EQ 和 SE 查询

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ondřej Čepek, James Weigle
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引用次数: 0

摘要

布尔函数的开关列表表示法(SLR)是布尔函数的压缩真值表表示法,其中只存储(i) 真值表中第一行的函数值和(ii) 开关列表。开关是一个布尔向量,其函数值不同于真值表中前一个布尔向量的值。Čepek 和 Chromý (JAIR 2020) 一文系统地研究了 SLR 的特性,并给出了 Darwiche 和 Marquis (JAIR 2002) 中介绍的知识编译图中所有标准查询的多项式时间算法。这些查询包括一致性检查、有效性检查、子句蕴涵检查、蕴涵检查、等价检查、句法蕴涵检查、模型计数和模型枚举。在知识编译图中,用最少的表示语言在多项式时间内支持的最困难的查询是有句蕴涵检查(等价检查是其特例)。如 Čepek 和 Chromý (JAIR 2020) 所示,对于 SLR,这一查询可以在多项式时间内得到回答。不过,该查询回答算法是一种间接算法:它首先将两个输入 SLR 编译成 OBDDs(必要时改变其中一个的变量顺序),然后使用 Wegener (2000) 专著中的算法对构建的 OBDDs(两者都遵守相同的变量顺序)进行句法蕴涵检查。在本文中,我们提出了通过处理输入 SLR(因此省去了编译成 OBDD 的步骤)直接回答等价性和有句蕴涵性查询的算法,在这两种情况下,对于 n 个变量的输入 SLR,回答查询的时间复杂度都提高了 n 倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A faster implementation of EQ and SE queries for switch-list representations

A switch-list representation (SLR) of a Boolean function is a compressed truth table representation of a Boolean function in which only (i) the function value of the first row in the truth table and (ii) a list of switches are stored. A switch is a Boolean vector whose function value differs from the value of the preceding Boolean vector in the truth table. The paper Čepek and Chromý (JAIR 2020) systematically studies the properties of SLRs and among other results gives polynomial-time algorithms for all standard queries investigated in the Knowledge Compilation Map introduced in Darwiche and Marquis (JAIR 2002). These queries include consistency check, validity check, clausal entailment check, implicant check, equivalence check, sentential entailment check, model counting, and model enumeration. The most difficult query supported in polynomial time by the smallest number of representation languages considered in the Knowledge Compilation Map is the sentential entailment check (of which the equivalence check is a special case). This query can be answered in polynomial time for SLRs, as shown in Čepek and Chromý (JAIR 2020). However, the query-answering algorithm is an indirect one: it first compiles both input SLRs into OBDDs (changing the order of variables for one of them if necessary) and then runs the sentential entailment check on the constructed OBDDs (both respecting the same order of variables) using an algorithm from the monograph by Wegener (2000). In this paper we present algorithms that answer both the equivalence and the sentential entailment query directly by manipulating the input SLRs (hence eliminating the compilation step into OBDD), which in both cases improves the time complexity of answering the query by a factor of n for input SLRs on n variables.

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来源期刊
Annals of Mathematics and Artificial Intelligence
Annals of Mathematics and Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
3.00
自引率
8.30%
发文量
37
审稿时长
>12 weeks
期刊介绍: Annals of Mathematics and Artificial Intelligence presents a range of topics of concern to scholars applying quantitative, combinatorial, logical, algebraic and algorithmic methods to diverse areas of Artificial Intelligence, from decision support, automated deduction, and reasoning, to knowledge-based systems, machine learning, computer vision, robotics and planning. The journal features collections of papers appearing either in volumes (400 pages) or in separate issues (100-300 pages), which focus on one topic and have one or more guest editors. Annals of Mathematics and Artificial Intelligence hopes to influence the spawning of new areas of applied mathematics and strengthen the scientific underpinnings of Artificial Intelligence.
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