On the disjunctive rational closure of a conditional knowledge base

IF 4.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Richard Booth , Ivan Varzinczak
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引用次数: 0

Abstract

One of the most widely investigated decision problems in symbolic AI is that of which conditional sentences of the form “if α, then normally β” should follow from a knowledge base containing this type of statements. Probably, the most notable approach to this problem is the rational closure construction put forward by Lehmann and Magidor in the'90s, which has been adapted to logical languages of various expressive powers since then. At the core of rational closure is the Rational Monotonicity property, which allows one to retain existing (defeasible) conclusions whenever new information cannot be negated by existing conclusions. As it turns out, Rational Monotonicity is not universally accepted, with many researchers advocating the investigation of weaker versions thereof leading to a larger class of consequence relations. A case in point is that of the Disjunctive Rationality property, which states that if one may draw a (defeasible) conclusion from a disjunction of premises, then one should be able to draw this conclusion from at least one of the premises taken alone. While there are convincing arguments that the rational closure forms the ‘simplest’ rational consequence relation extending a given set of conditionals, the question of what the simplest disjunctive consequence relation in this setting is has not been explored in depth. In this article, we do precisely that by motivating and proposing a concrete construction of the disjunctive rational closure of a conditional knowledge base, of which the properties and consequences of its adoption we also investigate in detail. (Previous versions of this work have been selected for presentation at the 18th International Workshop on Nonmonotonic Reasoning (NMR 2020) [1] and at the 35th AAAI Conference on Artificial Intelligence (AAAI 2021) [2]. The present submission extends and elaborates on both papers.)
论条件知识库的析取理性闭包
符号人工智能中最广泛研究的决策问题之一是“如果α,则通常β”形式的条件句应该从包含此类语句的知识库中跟随。对于这个问题,最值得注意的方法可能是莱曼和马吉多尔在90年代提出的理性闭包结构,从那时起,它就被适应于各种表达能力的逻辑语言。有理闭包的核心是有理单调性属性,它允许在现有结论不能否定新信息时保留现有的(可废止的)结论。事实证明,理性单调性并没有被普遍接受,许多研究人员提倡对其较弱版本的研究,从而导致更大的结果关系类别。一个恰当的例子是析取理性属性,它指出,如果一个人可以从前提的析取中得出(可推翻的)结论,那么他应该能够从至少一个单独的前提中得出这个结论。虽然有令人信服的论点认为,有理闭包形成了扩展给定条件集的“最简单”的理性推论关系,但在这种情况下,最简单的析取推论关系是什么这个问题还没有深入探讨。在本文中,我们正是通过激励和提出条件知识库的析取理性闭包的具体结构来做到这一点,我们还详细研究了其采用的性质和后果。(这项工作的先前版本已被选中在第18届非单调推理国际研讨会(NMR 2020)[1]和第35届AAAI人工智能会议(AAAI 2021)[2]上发表。本报告对这两篇论文进行了扩展和阐述。)
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
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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