Work

Collective Satisfaction Semantics for Opinion Based Argumentation

Year: 2024

Type: conference-paper

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.

DOI: 10.24963/kr.2024/59

Authors: Juliete Rossie, Jérôme Delobelle, Sébastien Konieczny, Clément Lens, Srdjan Vesic

Institutions: Centre National de la Recherche Scientifique, Centre de Recherche en Informatique de Lens, Université Paris Cité

Language: English

Topic: Multi-Agent Systems and Negotiation

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funder: Agence Nationale de la Recherche

Awards: An argumentation-based platform for e-democracy, Belief Change for Better Multi-Source Information Analysis

OpenAlex ID: W4403792821