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首页> 外文期刊>Inteligencia Artificial : Ibero-American Journal of Artificial Intelligence >Rational versus Intuitive Outcomes of Reasoning with Preferences: Argumentation Perspective
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Rational versus Intuitive Outcomes of Reasoning with Preferences: Argumentation Perspective

机译:具有偏好的推理的理性与直觉结果:论证视角

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Reasoning with preference information is a common human activity. As modelling human reasoning is one of the main objectives of AI, reasoning with preferences is an important topic in various elds of AI, such as Knowledge Representation and Reasoning (KR). Argumentation is one particular branch of KR that concerns, among other tasks, modelling common-sense reasoning with preferences. A key issue there, is the lack of consensus on how to deal with preferences. Witnessing this is a multitude of proposals on how to formalise reasoning with preferences in argumentative terms. As a commonality, however, formalisms of argumentation with preferences tend to ful l various criteria of `rational' reasoning, notwithstanding the fact that human reasoning is often not `rational', yet seemingly `intuitive'. In this paper, we study how several formalisms of argumentation with preferences model human intuition behind a particular common-sense reasoning problem. More speci cally, we present a common-sense scenario of reasoning with rules and preferences, complemented with a survey of decisions made by human respondents that indicates an `intuitive' solution, and analyse how this problem is tackled in argumentation. We conclude that most approaches to argumentation with preferences a ord a `rational' solution to the problem, and discuss one recent formalism that yields the `intuitive' solution instead. We argue that our results call for advancements in the area of argumentation with preferences in particular, as well as for further studies of reasoning with preferences in AI at large.
机译:具有偏好信息的推理是人类的常见活动。由于建模人类推理是AI的主要目标之一,因此具有偏好的推理是AI各个领域(例如知识表示和推理(KR))的重要主题。论证是KR的一个特定分支,除其他任务外,还涉及使用偏好对常识推理进行建模。那里的一个关键问题是,在如何处理偏好方面缺乏共识。目睹这一点的是关于如何用论据上的偏好来规范推理的众多建议。然而,作为共性,尽管人们的推理通常不是“理性的”,而是貌似“直观的”,但带有偏好的论证形式主义倾向于满足“理性”推理的各种标准。在本文中,我们研究了几种带有偏好的论证形式主义如何在特定常识性推理问题背后模拟人类的直觉。更具体地说,我们提出了一种常识性的规则和偏好推理场景,辅之以人类受访者做出的决策调查,该调查表明了“直觉”的解决方案,并分析了如何在论证中解决该问题。我们得出的结论是,大多数带有偏好的论证方法都是对问题的“理性”解决方案,并讨论了一种最新的形式主义,它反而产生了“直观”解决方案。我们认为,我们的结果要求在特别是具有偏好的论证领域取得进步,并且需要在整个AI中进一步研究具有偏好的推理。

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