认识论逻辑程序:一些属性的研究

IF 1.4 2区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
STEFANIA COSTANTINI, ANDREA FORMISANO
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引用次数: 0

摘要

认识论逻辑程序(ELPs)是答案集编程(ASP)的扩展,带有认识论运算符。这类程序的语义是以世界观的形式提供的,世界观是信念集的集合,也就是语法上的原子集的集合。不同的语义方法提出了不同的世界观特征。最近的研究引入了任何 ELP 语义都应满足的语义属性,如认识分裂属性(Epistemic Splitting Property),如果满足该属性,就能以自下而上的方式模块化地计算世界观,类似于 "传统 "的 ASP。我们分析了改变视角的可能性,即从自下而上转向自上而下的分裂方法。我们提出了一种自上而下的基本方法,并证明它等同于自下而上的方法。然后,我们提出了一种扩展方法,在这种方法中,我们的新定义:(i) 可证明适用于许多现有语义;(ii) 与 "传统 "ASP 运作类似;(iii) 在任何语义下都可证明与自下而上的拆分概念重合,至少在认识论分层程序类(直观地说,就是那些认识论算子的使用被分层的程序)上是如此;(iv) 更好地遵循常见的 ASP 编程方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Epistemic Logic Programs: A Study of Some Properties

Epistemic logic programs (ELPs), extend answer set programming (ASP) with epistemic operators. The semantics of such programs is provided in terms of world views, which are sets of belief sets, that is, syntactically, sets of sets of atoms. Different semantic approaches propose different characterizations of world views. Recent work has introduced semantic properties that should be met by any semantics for ELPs, like the Epistemic Splitting Property, that, if satisfied, allows to modularly compute world views in a bottom-up fashion, analogously to “traditional” ASP. We analyze the possibility of changing the perspective, shifting from a bottom-up to a top-down approach to splitting. We propose a basic top-down approach, which we prove to be equivalent to the bottom-up one. We then propose an extended approach, where our new definition: (i) is provably applicable to many of the existing semantics; (ii) operates similarly to “traditional” ASP; (iii) provably coincides under any semantics with the bottom-up notion of splitting at least on the class of Epistemically Stratified Programs (which are, intuitively, those where the use of epistemic operators is stratified); (iv) better adheres to common ASP programming methodology.

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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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