An empirical and axiomatic comparison of ranking-based semantics for abstract argumentation

Elise Bonzon (1, 2) , Jérôme Delobelle (2) , Sébastien Konieczny (3, 4) , Nicolas Maudet (5)

1 Université Paris Descartes, Sorbonne Paris Cité
2 LIPADE (URP_2517) - Laboratoire d'Informatique Paris Descartes
3 CNRS - Centre National de la Recherche Scientifique
4 CRIL - Centre de Recherche en Informatique de Lens
5 SMA - Systèmes Multi-Agents

Argumentation is the process of evaluating and comparing a set of arguments. A way to compare them consists in using a ranking-based semantics which rank-order arguments from the most to the least acceptable ones. Recently, a number of such semantics have been proposed independently, often associated with some desirable properties. In this work, we provide a thorough analysis of ranking-based semantics in two different ways. The first is an empirical comparison on randomly generated argumentation frameworks which reveals insights into similarities and differences between ranking-based semantics. The second is an axiomatic comparison of all these semantics with respect to the proposed properties aiming to better understand the behaviour of each semantics.

Keywords: abstract argumentation; ranking-based semantics; comparison

Domains: Artificial Intelligence [cs.AI]

Elise Bonzon, Jérôme Delobelle, Sébastien Konieczny, Nicolas Maudet. An empirical and axiomatic comparison of ranking-based semantics for abstract argumentation. Journal of Applied Non-Classical Logics, 2023, 33 (3-4), pp.328-386. ⟨10.1080/11663081.2023.2246863⟩. ⟨hal-04189781⟩