具有有序位错的逻辑程序优选模型的一个逻辑表征

IF 1.4 2区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
A. Charalambidis, P. Rondogiannis, Antonis Troumpoukis
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引用次数: 2

摘要

摘要有序析取逻辑程序是对经典逻辑程序的扩展,它具有在程序规则头部表示具有递减偏好度的可选方案的能力。尽管有序析取的运算意义是明确的,但它的语义存在一个重要的开放性问题。特别是,不存在一种纯粹的模型理论方法来确定LPOD的最优选模型。目前,最优选模型的选择是使用一种技术来执行的,这种技术不是完全基于程序的模型,在某些情况下产生反直觉的结果。我们为LPODs提供了一种新颖的模型理论语义,它使用一个额外的真值来识别程序的最优选模型。我们证明了所提出的方法克服了lpod传统语义的缺点。此外,新方法可用于定义自然类逻辑程序的语义,这些逻辑程序可以在子句头部同时具有有序和经典析取。这使得程序不仅可以表达严格级别的偏好,还可以表达同等偏好的替代方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Logical Characterization of the Preferred Models of Logic Programs with Ordered Disjunction
Abstract Logic programs with ordered disjunction (LPODs) extend classical logic programs with the capability of expressing alternatives with decreasing degrees of preference in the heads of program rules. Despite the fact that the operational meaning of ordered disjunction is clear, there exists an important open issue regarding its semantics. In particular, there does not exist a purely model-theoretic approach for determining the most preferred models of an LPOD. At present, the selection of the most preferred models is performed using a technique that is not based exclusively on the models of the program and in certain cases produces counterintuitive results. We provide a novel, model-theoretic semantics for LPODs, which uses an additional truth value in order to identify the most preferred models of a program. We demonstrate that the proposed approach overcomes the shortcomings of the traditional semantics of LPODs. Moreover, the new approach can be used to define the semantics of a natural class of logic programs that can have both ordered and classical disjunctions in the heads of clauses. This allows programs that can express not only strict levels of preferences but also alternatives that are equally preferred.
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来源期刊
Theory and Practice of Logic Programming
Theory and Practice of Logic Programming 工程技术-计算机:理论方法
CiteScore
4.50
自引率
21.40%
发文量
40
审稿时长
>12 weeks
期刊介绍: Theory and Practice of Logic Programming emphasises both the theory and practice of logic programming. Logic programming applies to all areas of artificial intelligence and computer science and is fundamental to them. Among the topics covered are AI applications that use logic programming, logic programming methodologies, specification, analysis and verification of systems, inductive logic programming, multi-relational data mining, natural language processing, knowledge representation, non-monotonic reasoning, semantic web reasoning, databases, implementations and architectures and constraint logic programming.
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