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International Conference on Principles and Practice of Multi-Agent Systems

PRIMA 2018: PRIMA 2018: Principles and Practice of Multi-Agent Systems pp 331–343Cite as

Abstract Argumentation / Persuasion / Dynamics

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11224))

Abstract

The act of persuasion, a key component in rhetoric argumentation, may be viewed as a dynamics modifier. We extend Dung’s frameworks with acts of persuasion among agents, and consider interactions among attack, persuasion and defence that have been largely unheeded so far. We characterise basic notions of admissibilities in this framework, and show a way of enriching them through, effectively, CTL (computation tree logic) encoding, which also permits importation of the theoretical results known to the logic into our argumentation frameworks. Our aim is to complement the growing interest in coordination of static and dynamic argumentation.

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Notes

  1. 1.

    We assume the standard notion of occurrence.

  2. 2.

    The liberty of allowing arguments into \(\mathcal {M}\) causes no confusion, let alone issues. If one is so inclined, he/she may choose to consider that components of \(\delta \) that appear in \(\mathcal {M}\) are semantic counterparts of those that appear in the syntax of CTL with one-to-one correspondence between them.

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Acknowledgements

We thank anonymous reviewers for helpful comments. There was one suggestion concerning terms: to say to “convince” instead of “actively persuade” or “convert”. We seriously contemplated the suggested modification, and only in the end chose to leave the text as it was.

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Authors and Affiliations

  1. National Institute of Informatics, Chiyoda, Japan

    Ryuta Arisaka & Ken Satoh

Authors
  1. Ryuta Arisaka
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  2. Ken Satoh
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Correspondence to Ryuta Arisaka .

Editor information

Editors and Affiliations

  1. School of Computing and Information Systems, University of Melbourne, Melbourne, Australia

    Tim Miller

  2. Department of Computer Science, University of Aberdeen, Aberdeen, UK

    Nir Oren

  3. Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan

    Yuko Sakurai

  4. Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

    Itsuki Noda

  5. University of Otago, Dunedin, New Zealand

    Bastin Tony Roy Savarimuthu

  6. Computer Science Department, New Mexico State University, Las Cruces, USA

    Tran Cao Son

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Arisaka, R., Satoh, K. (2018). Abstract Argumentation / Persuasion / Dynamics. In: Miller, T., Oren, N., Sakurai, Y., Noda, I., Savarimuthu, B.T.R., Cao Son, T. (eds) PRIMA 2018: Principles and Practice of Multi-Agent Systems. PRIMA 2018. Lecture Notes in Computer Science(), vol 11224. Springer, Cham. https://doi.org/10.1007/978-3-030-03098-8_20

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  • DOI: https://doi.org/10.1007/978-3-030-03098-8_20

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  • Print ISBN: 978-3-030-03097-1

  • Online ISBN: 978-3-030-03098-8

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