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Dynamics of Fuzzy Argumentation Frameworks

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Logic and Argumentation (CLAR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12061))

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Abstract

Dung’s theory of abstract argumentation plays an incremental role in artificial intelligence. The research about the dynamics theory of argumentation efficiently identifies the justified arguments when arguments or attacks change. However, the dynamics theory is absent in fuzzy argumentation framework (FAF). We want to calculate the semantics of the updated FAF by partially reusing the semantics of the previous FAF. In this paper, we explore the dynamics theory in FAFs. First, we introduce all the changes of FAF, including not only the changes of arguments and attacks but also the increases or decreases of their fuzzy degrees. Thus, the changes in FAFs are more complicated than standard AF. Then by extending Liao’s division-based approach, we provide an efficient algorithm for computing some basic semantics. This algorithm conserves part of the semantics in the previous FAF. Thus, we can efficiently compute the belief degree to which arguments are justified.

This work is supported by the National Natural Science Foundation of China (11601288), the Natural Science Foundation of Shandong (ZR2016AQ21) and the Excellent Young Scholars Research Fund of Shandong Normal University.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Shandong Normal University, Jinan, 250300, Shandong, China

    Zongshun Wang & Jiachao Wu

Authors
  1. Zongshun Wang
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  2. Jiachao Wu
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Correspondence to Jiachao Wu .

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Editors and Affiliations

  1. Utrecht University, Utrecht, Utrecht, The Netherlands

    Mehdi Dastani

  2. Zhejiang University, Hangzhou, China

    Huimin Dong

  3. University of Luxembourg, Luxembourg, Luxembourg

    Leon van der Torre

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Wang, Z., Wu, J. (2020). Dynamics of Fuzzy Argumentation Frameworks. In: Dastani, M., Dong, H., van der Torre, L. (eds) Logic and Argumentation. CLAR 2020. Lecture Notes in Computer Science(), vol 12061. Springer, Cham. https://doi.org/10.1007/978-3-030-44638-3_18

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  • DOI: https://doi.org/10.1007/978-3-030-44638-3_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-44637-6

  • Online ISBN: 978-3-030-44638-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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