Identifying roles of formulas in inconsistency under Priest's minimally inconsistent logic of paradox

IF 5.1 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence Pub Date : 2024-08-05 DOI:10.1016/j.artint.2024.104199
Kedian Mu
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Abstract

It has been increasingly recognized that identifying roles of formulas of a knowledge base in the inconsistency of that base can help us better look inside the inconsistency. However, there are few approaches to identifying such roles of formulas from a perspective of models in some paraconsistent logic, one of typical tools used to characterize inconsistency in semantics. In this paper, we characterize the role of each formula in the inconsistency arising in a knowledge base from informational as well as causal aspects in the framework of Priest's minimally inconsistent logic of paradox. At first, we identify the causal responsibility of a formula for the inconsistency based on the counterfactual dependence of the inconsistency on the formula under some contingency in semantics. Then we incorporate the change on semantic information in the framework of causal responsibility to develop the informational responsibility of a formula for the inconsistency to capture the contribution made by the formula for the inconsistent information. This incorporation makes the informational responsibility interpretable from the point of view of causality, and capable of catching the role of a formula in inconsistent information concisely. In addition, we propose notions of naive and quasi naive responsibilities as two auxiliaries to describe special relations between inconsistency and formulas in semantic sense. Some intuitive and interesting properties of the two kinds of responsibilities are also discussed.

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在普里斯特的悖论最小不一致逻辑中确定公式在不一致中的作用
越来越多的人认识到,识别知识库的公式在该知识库的不一致性中所起的作用,可以帮助我们更好地观察不一致性的内部。然而,从准一致逻辑模型的角度来识别公式的这种作用的方法还很少,而准一致逻辑是用来描述语义学中不一致现象的典型工具之一。本文在普里斯特最小不一致悖论逻辑的框架内,从信息和因果两个方面描述了每个公式在知识库中产生的不一致中的作用。首先,我们根据不一致性在语义上的某种偶然性下对公式的反事实依赖性来确定公式对不一致性的因果责任。然后,我们将语义信息的变化纳入因果责任的框架,发展出公式对不一致的信息责任,以捕捉公式对不一致信息所做的贡献。这种结合使得信息责任可以从因果关系的角度进行解释,并能简明地捕捉公式在不一致信息中的作用。此外,我们还提出了 "天真责任 "和 "准天真责任 "这两个辅助概念,以描述不一致与公式在语义上的特殊关系。我们还讨论了这两种责任的一些直观而有趣的特性。
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来源期刊
Artificial Intelligence
Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
11.20
自引率
1.40%
发文量
118
审稿时长
8 months
期刊介绍: The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.
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