KR2024Proceedings of the 21st International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning

Hanoi, Vietnam. November 2-8, 2024.

Edited by

ISSN: 2334-1033
ISBN: 978-1-956792-05-8

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Copyright © 2024 International Joint Conferences on Artificial Intelligence Organization

Collective Satisfaction Semantics for Opinion Based Argumentation

  1. Juliete Rossie(CNRS)
  2. Jérôme Delobelle(Université Paris Cité)
  3. Sébastien Konieczny(CRIL - CNRS)
  4. Clément Lens(CRIL)
  5. Srdjan Vesic(CNRS)

Keywords

  1. Argumentation-General

Abstract

Voting on arguments in a debate is a natural approach for reaching a consensual decision. Despite this, there are few formal methods of abstract argumentation dealing with the use of votes in the process of selecting accepted arguments. We introduce the Opinion Based Argumentation (OBA) framework, where individuals can vote (or abstain) for or against arguments in a Dung argumentation framework. Our research aims to determine the most appropriate collective decisions within this framework. We propose a new semantics for this framework, called Collective Satisfaction Semantics (CSS), to evaluate the acceptability of arguments and study their properties. Additionally, we compare these semantics against alternative methods adapted from related literature to provide insights into their relative effectiveness.