Acceptability Semantics for Weighted Argumentation Frameworks

Leila Amgoud (1, 2) , Jonathan Ben-Naim (3) , Dragan Doder (1) , Srdjan Vesic (4)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
2 CNRS - Centre National de la Recherche Scientifique
3 LIF - Laboratoire d'informatique Fondamentale de Marseille - UMR 6166
4 CRIL - Centre de Recherche en Informatique de Lens

The paper studies semantics that evaluate arguments in argumentation graphs, where each argument has a basic strength, and may be attacked by other arguments. It starts by defining a set of principles , each of which is a property that a semantics could satisfy. It provides the first formal analysis and comparison of existing semantics. Finally, it defines three novel semantics that satisfy more principles than existing ones.

Mots clés: Computational models of Argument

Domaines: Intelligence artificielle [cs.AI]

Leila Amgoud, Jonathan Ben-Naim, Dragan Doder, Srdjan Vesic. Acceptability Semantics for Weighted Argumentation Frameworks. Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI 2017), Aug 2017, Melbourne, Australia. ⟨10.24963/ijcai.2017/9⟩. ⟨hal-02326004⟩