Argumentation framework with fuzzy preference relations

Authors:
Souhila Kaci;Christophe Labreuche
Affiliations:
Université Lille-Nord de France, Artois, CRIL, CNRS, UMR, France and CLLE, LTC, CNRS, UMR, Toulouse Cedex 9, France;Thales Research & Technology, Palaiseau Cedex, France
Venue:
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Year:
2010

Citing 5
Cited 1

A mathematical treatment of defeasible reasoning and its implementation

Artificial Intelligence
On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games

Artificial Intelligence
Inferring from Inconsistency in Preference-Based Argumentation Frameworks

Journal of Automated Reasoning
Preference-based argumentation: Arguments supporting multiple values

International Journal of Approximate Reasoning
Inconsistency tolerance in weighted argument systems

Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2

Preferences in AI: An overview

Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Dung's argumentation developed in Artificial Intelligence is based on a binary attack relation. An important particular case arises when there is a Boolean preference relation between the arguments. We propose to extend this argumentation framework to a fuzzy preference relation. This implies that an argument can attack another one to a certain degree. It turns out that the acceptability semantics in this new framework can be obtained in two ways: either from the concept of fuzzy kernel defined in fuzzy preference modeling, or from the acceptability semantics defined on weighted attack relations. Finally, we obtain some requirements on the fuzzy preference relation in the case when it shall be constructed from weights assigned to the arguments.