A quantitative preference-based structured argumentation system for decision support

We introduce in this paper a quantitative preference based argumentation system relying on ASPIC argumentation framework [1] and fuzzy set theory. The knowledge base is fuzzified to allow agents expressing their expertise (premises and rules) attached with grades of importance in the unit interval. Arguments are then attached with a strength score aggregating the importance expressed on their premises and rules. Extensions, corresponding to subsets of consistent arguments, are also attached with forces computed based on their strong arguments. The forces are used then to rank extensions from the strongest to the weakest one, upon which decisions can be made. We have also shown that the strength preference relation defined over arguments is reasonable [2] and our fuzzy ASPIC argumentation system can be seen as a computationally efficient instantiation of the generic model of structured argumentation framework introduced in [2].

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