Explainable Logic-Based Argumentation

Ofer Arieli, AnneMarie Borg, Matthis Hesse, Christian Straßer

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    Explainable artificial intelligence (XAI) has gained increasing interest in recent years in the argumentation community. In this paper we consider this topic in the context of logic-based argumentation, showing that the latter is a particularly promising paradigm for facilitating explainable AI. In particular, we provide two representations of abductive reasoning by sequent-based argumentation frameworks and show that such frameworks successfully cope with related challenges, such as the handling of synonyms, justifications, and logical equivalences.
    Original languageEnglish
    Title of host publicationComputational Models of Argument
    EditorsFrancesca Toni, Sylwia Polberg, Richard Booth, Martin Caminada, Hiroyuki Kido
    PublisherIOS Press
    Pages32-43
    Number of pages12
    ISBN (Electronic)978-1-64368-307-2
    ISBN (Print)978-1-64368-306-5
    DOIs
    Publication statusPublished - 7 Sept 2022

    Publication series

    NameFrontiers in Artificial Intelligence and Applications
    PublisherIOS Press
    Volume353
    ISSN (Print)0922-6389
    ISSN (Electronic)1879-8314

    Bibliographical note

    Funding Information:
    1Supported by the Israel Science Foundation (grant 550/19).

    Publisher Copyright:
    © 2022 The authors and IOS Press. All rights reserved.

    Keywords

    • Explainable AI
    • sequent-based argumentation
    • abductive logics

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