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Preference Elicitation in Assumption-Based Argumentation

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PRIMA 2020: Principles and Practice of Multi-Agent Systems (PRIMA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12568))

Abstract

Various structured argumentation frameworks utilize preferences as part of their inference procedure. In this paper, we consider an inverse of the standard reasoning problem, seeking to identify what preferences could lead to a given set of conclusions being drawn. We ground our work in the Assumption-Based Argumentation (ABA) framework, and present an algorithm which computes and enumerates all possible sets of preferences (restricted to three identified cases) over the assumptions in the system from which a desired conflict-free set of conclusions can be obtained under a given semantics. After describing our algorithm, we establish its soundness, completeness and complexity.

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Notes

  1. 1.

    We only consider flat ABA frameworks, where assumptions cannot be deduced from other assumptions.

  2. 2.

    Due to space restrictions we only demonstrate this on preferred extensions, but the approach works on all conflict-free extensions.

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Acknowledgements

This work was supported by EPSRC grant (EP/P011829/1), Supporting Security Policy with Effective Digital Intervention (SSPEDI).

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Authors and Affiliations

  1. Department of Informatics, King’s College London, London, UK

    Quratul-ain Mahesar

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

    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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Correspondence to Quratul-ain Mahesar .

Editor information

Editors and Affiliations

  1. Nagoya Institute of Technology, Nagoya, Japan

    Takahiro Uchiya

  2. University of Tasmania, Tasmania, TAS, Australia

    Quan Bai

  3. University of Alcalá, Alcala de Henares, Spain

    Iván Marsá Maestre

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Mahesar, Qa., Oren, N., Vasconcelos, W.W. (2021). Preference Elicitation in Assumption-Based Argumentation. In: Uchiya, T., Bai, Q., Marsá Maestre, I. (eds) PRIMA 2020: Principles and Practice of Multi-Agent Systems. PRIMA 2020. Lecture Notes in Computer Science(), vol 12568. Springer, Cham. https://doi.org/10.1007/978-3-030-69322-0_13

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  • DOI: https://doi.org/10.1007/978-3-030-69322-0_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-69321-3

  • Online ISBN: 978-3-030-69322-0

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