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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 616))

Abstract

One of the main objectives of AI is modelling human reasoning. Since preference information is an indispensable component of common-sense reasoning, the two should be studied in tandem. Argumentation is an established branch of AI dedicated to this task. In this paper, we study how argumentation with preferences models human intuition behind a particular decision making scenario concerning reasoning with rules and preferences. To this end, we present an example of a common-sense reasoning problem complemented with a survey of decisions made by human respondents. The survey reveals an answer that contrasts with solutions offered by various argumentation formalisms. We argue that our results call for advancements of approaches to argumentation with preferences as well as for examination of the type of problems of reasoning with preferences put forward in this paper. Our work contributes to the line of research on preference handling in argumentation, and it also enriches the discussions on the increasingly important topic of preference treatment in AI at large.

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Notes

  1. 1.

    Since all three cakes are wanted, condition (a) simply indicates that the first round decision is pivotal and involves basically only one rule expressed in condition (b).

  2. 2.

    The survey results can be found at https://www.surveymonkey.com/results/SM-GLNNBZ8Q/. We have surveyed PhD students at the Department of Computing, Imperial College London. Invitations to take the survey were distributed by email via the Department’s PhD students’ mailing list. 79 responses were obtained in a single day. We do not claim any statistically significant findings.

  3. 3.

    By definition, there are infinitely many arguments, but it suffices to consider only a finite number of them, as they represent the essential information; see [9] for details.

  4. 4.

    Two types of rules are commonly used in argumentation: strict rules, whose consequent necessarily follows from the antecedent; and defeasible rules, whose consequent normally (e.g. unless there are exceptions to the rule) follows from the antecedent.

  5. 5.

    For \(\varphi \in \mathcal {L}\), its complement \(-\varphi \) is: \(\lnot \psi \) if \(\varphi = \psi \); and \(\psi \) if \(\varphi = \lnot \psi \).

  6. 6.

    For simplicity, we omit the precise definitions of the consequence operator as well as the relation \(\sqsubseteq \); see [35, 37] for details.

  7. 7.

    With the attack relation specified next, this simplification is meant purely to make the argument framework easier to read.

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Čyras, K. (2016). Argumentation-Based Reasoning with Preferences. In: Bajo, J., et al. Highlights of Practical Applications of Scalable Multi-Agent Systems. The PAAMS Collection. PAAMS 2016. Communications in Computer and Information Science, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-39387-2_17

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