摘要论证与答案集规划:纳尔逊逻辑的两面

IF 1.4 2区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Theory and Practice of Logic Programming Pub Date : 2022-05-03 DOI:10.1017/s1471068422000114
JORGE FANDINNO, LUIS FARIÑAS DEL CERRO
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引用次数: 0

摘要

在这项工作中,我们证明了逻辑编程和抽象论证框架都可以用Nelson的构造逻辑N4来解释。在这种逻辑中,我们通过形式化我们称之为非矛盾推理和强化封闭世界假设的两个原则来做到这一点:第一个原则表明,任何信念都不能建立在相互矛盾的证据之上,而后者则迫使未知和矛盾的证据都被视为错误。使用这些原则,逻辑编程和抽象论证框架都以模块化的方式和使用对象语言转换为建设性逻辑。逻辑规划蕴涵和抽象论证支持在翻译中遵循非矛盾推理原则成为一种新的蕴涵联系。然后,攻击通过将这种新的暗示与强烈的否定结合起来来表现。逻辑规划理论与实践的思考。
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Abstract Argumentation and Answer Set Programming: Two Faces of Nelson’s Logic

In this work, we show that both logic programming and abstract argumentation frameworks can be interpreted in terms of Nelson’s constructive logic N4. We do so by formalising, in this logic, two principles that we call noncontradictory inference and strengthened closed world assumption: the first states that no belief can be held based on contradictory evidence while the latter forces both unknown and contradictory evidence to be regarded as false. Using these principles, both logic programming and abstract argumentation frameworks are translated into constructive logic in a modular way and using the object language. Logic programming implication and abstract argumentation supports become, in the translation, a new implication connective following the noncontradictory inference principle. Attacks are then represented by combining this new implication with strong negation. Under consideration in Theory and Practice of Logic Programming (TPLP).

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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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