Fuzzy Argumentation System for Decision Support

Abstract

We introduce in this paper a quantitative preference based argumentation system relying on ASPIC argumentation framework and fuzzy set theory. The knowledge base is fuzzified to allow the experts to express their expertise (premises and rules) attached with grades of importance in the unit interval. Arguments are attached with a score aggregating the importance expressed on their premises and rules. Extensions are then computed and the strength of each of which can also be obtained based on its strong arguments. The strengths are used to rank fuzzy extensions from the strongest to the weakest one, upon which decisions can be made. The approach is finally used for decision making in a real world application within the EcoBioCap project. © Springer International Publishing Switzerland 2014.