On Nested Justification Systems

IF 1.4 2区数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Theory and Practice of Logic Programming Pub Date : 2022-07-11 DOI:10.1017/S1471068422000266

Simon Marynissen, J. Heyninck, B. Bogaerts, M. Denecker

引用次数: 2

Abstract

Abstract Justification theory is a general framework for the definition of semantics of rule-based languages that has a high explanatory potential. Nested justification systems, first introduced by Denecker et al., allow for the composition of justification systems. This notion of nesting thus enables the modular definition of semantics of rule-based languages, and increases the representational capacities of justification theory. As we show in this paper, the original characterization of semantics for nested justification systems leads to the loss of information relevant for explanations. In view of this problem, we provide an alternative characterization of their semantics and show that it is equivalent to the original one. Furthermore, we show how nested justification systems allow representing fixpoint definitions.

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关于嵌套论证系统

正当性理论是规则语言语义定义的一般框架，具有很高的解释力。嵌套论证系统，首先由Denecker等人介绍，允许论证系统的组成。因此，嵌套的概念使基于规则的语言的语义的模块化定义成为可能，并增加了证明理论的表示能力。正如我们在本文中所展示的那样，嵌套论证系统的原始语义特征导致了与解释相关的信息的丢失。针对这一问题，我们给出了它们语义的另一种表征，并证明了它与原来的语义等价。此外，我们还展示了嵌套调整系统如何允许表示固定点定义。

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

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

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.