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Disjunctive closures for knowledge compilation

机译:知识汇编的析取闭包

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The knowledge compilation (KC) map can be viewed as a multi-criteria evaluation of a number of target classes of representations for propositional KC. Using this map, the choice of a class for a given application can be made, considering both the space efficiency of it (i.e., its ability to represent information using little space), and its time efficiency, i.e., the queries and transformations which can be achieved in polynomial time, among those of interest for the application under consideration. When no class of propositional representations offers all the transformations one would expect, some of them can be left implicit. This is the key idea underlying the concept of closure introduced here: instead of performing computationally expensive transformations, one just remembers that they have to be done. In this paper, we investigate the disjunctive closure principles, i.e., disjunction, existential quantification, and their combinations. We provide several characterization results concerning the corresponding closures. We also extend the KC map with new propositional languages obtained as disjunctive closures of several incomplete propositional languages, including the well-known KROM (the CNF formulae containing only binary clauses), HORN (the CNF formulae containing only Horn clauses), and AFF (the affine language, which is the set of conjunctions of XOR-clauses). Each introduced language is evaluated along the lines of the KC map.
机译:知识汇编(KC)图可以视为对命题KC的表示形式的多个目标类的多标准评估。使用该映射,既可以考虑给定应用程序的空间效率(即,它使用很少的空间表示信息的能力),也可以考虑其时间效率,即可以进行查询和转换的类,从而为给定应用程序选择类。在考虑中的应用感兴趣的多项式中,可以在多项式时间内实现。当没有一类命题表示形式提供人们所期望的所有转换时,其中一些可以隐含。这是这里介绍的闭包概念的基础的关键思想:与其执行计算量大的转换,还不如说必须完成转换。在本文中,我们研究了析取闭包原理,即析取,存在量化及其组合。我们提供了一些与相应闭包有关的表征结果。我们还将KC图扩展为新的命题语言,这些命题语言是几种不完整命题语言的析取闭合而获得的,包括众所周知的KROM(仅包含二进制子句的CNF公式),HORN(仅包含Horn子句的CNF公式)和AFF(仿射语言,这是XOR子句的连词集)。每种引入的语言都按照KC地图的方式进行评估。

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