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Computing Preferences in Abstract Argumentation

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PRIMA 2018: Principles and Practice of Multi-Agent Systems (PRIMA 2018)

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

Abstract

We present an extension-based approach for computing preferences in an abstract argumentation system. Although numerous argumentation semantics have been developed previously for identifying acceptable sets of arguments from an argumentation framework, there is a lack of justification behind their acceptability based on implicit argument preferences. This paper presents a novel algorithm for exhaustively computing and enumerating all possible sets of preferences for a conflict-free set of arguments in an abstract argumentation framework. We prove the soundness and completeness of the algorithm. The research establishes that preferences are determined using an extension-based approach after the evaluation phase (acceptability of arguments) rather than stated beforehand. We also present some novel insights by comparing the computed preferences for the extensions.

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Notes

  1. 1.

    This means it could be either \(C>B\) or \(C=B\).

  2. 2.

    This means it could be either \(A>B\) or \(A=B\), and similarly \(D>E\) or \(D=E\).

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Acknowledgments

Financial support from The UK Engineering and Physical Sciences Research Council (EPSRC) for the grant (EP/P011829/1), Supporting Security Policy with Effective Digital Intervention (SSPEDI) is gratefully acknowledged.

Author information

Authors and Affiliations

  1. Department of Computing Science, University of Aberdeen, Aberdeen, UK

    Quratul-ain Mahesar, Nir Oren & Wamberto W. Vasconcelos

Authors
  1. Quratul-ain Mahesar
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  2. Nir Oren
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  3. Wamberto W. Vasconcelos
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Corresponding author

Correspondence to Quratul-ain Mahesar .

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

Appendix

Appendix

Table 3. Preference sets for all conflict-free extensions
Full size table

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Mahesar, Qa., Oren, N., Vasconcelos, W.W. (2018). Computing Preferences in Abstract Argumentation. 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_24

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  • DOI: https://doi.org/10.1007/978-3-030-03098-8_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03097-1

  • Online ISBN: 978-3-030-03098-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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