Fuzzy labeling for argumentation frameworks

Authors:
Cristian Gratie;Adina Magda Florea
Affiliations:
AI-MAS Laboratory, Computer Science Department, University;AI-MAS Laboratory, Computer Science Department, University
Venue:
ArgMAS'11 Proceedings of the 8th international conference on Argumentation in Multi-Agent Systems
Year:
2011

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Abstract

This paper introduces the use of fuzzy labels in argumentation. The first approach we propose is built as a natural extension of the in, out, undec labeling to real valued labels, coupled with an unsupervised learning algorithm that assigns consistent labels starting from a random initial assignment. The second approach regards argument (fuzzy) labels as degrees of certitude in the argument's acceptability. This translates into a system of equations that provides among its solutions the labelings that describe complete extensions.