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Handling Heterogeneous Disagreements Through Abstract Argumentation (Extended Abstract)

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PRIMA 2017: Principles and Practice of Multi-Agent Systems (PRIMA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10621))

Abstract

Agents disagree in many situations and in many ways on their beliefs, preferences and goals. Abstract argumentation frameworks are a formal model to handle disagreement, which is represented as a conflict relation between a set of arguments. To solve the conflict and identify justified arguments, a single argumentation semantics is applied at a global level, under the assumption that the involved conflicts are essentially homogeneous. In the talk I will argue that disagreements are in general heterogeneous and thus should be treated in different ways according both to their nature and to the specific agents features. Accordingly, a general model of abstract argumentation will be discussed, able to handle heterogeneous disagreements by means of multiple argumentation semantics at a local level.

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Notes

  1. 1.

    The reader is referred to [3] for an introduction to argumentation semantics also including additional proposals.

  2. 2.

    This has been first proposed in [17] and called sorting.

  3. 3.

    Focusing on extension-based semantics, this has been called Uniform Case Extension Equivalence in [17].

  4. 4.

    More precisely, given a labelling \({\mathcal {L}}\) and a set of arguments \(\mathcal {A} rgs \), \({{\mathcal {L}}}{\downarrow _{\mathcal {A} rgs }} \equiv {\mathcal {L}}\cap (\mathcal {A} rgs \times \{\mathtt {in},\mathtt {out},\mathtt {undec}\})\).

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Correspondence to Massimiliano Giacomin .

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Giacomin, M. (2017). Handling Heterogeneous Disagreements Through Abstract Argumentation (Extended Abstract). In: An, B., Bazzan, A., Leite, J., Villata, S., van der Torre, L. (eds) PRIMA 2017: Principles and Practice of Multi-Agent Systems. PRIMA 2017. Lecture Notes in Computer Science(), vol 10621. Springer, Cham. https://doi.org/10.1007/978-3-319-69131-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-69131-2_1

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