Fuzzy Labeling for Abstract Argumentation: An Empirical Evaluation

  • Célia da Costa Pereira
  • Mauro Dragoni
  • Andrea G. B. Tettamanzi
  • Serena Villata
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9858)

Abstract

Argumentation frameworks have to be evaluated with respect to argumentation semantics to compute the set(s) of accepted arguments. In a previous approach, we proposed a fuzzy labeling algorithm for computing the (fuzzy) set of acceptable arguments, when the sources of the arguments in the argumentation framework are only partially trusted. The convergence of the algorithm was proved, and the convergence speed was estimated to be linear, as it is generally the case with iterative methods. In this paper, we provide an experimental validation of this algorithm with the aim of carrying out an empirical evaluation of its performance on a benchmark of argumentation graphs. Results show the satisfactory performance of our algorithm, even on complex graph structures as those present in our benchmark.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Célia da Costa Pereira
    • 1
  • Mauro Dragoni
    • 2
  • Andrea G. B. Tettamanzi
    • 1
  • Serena Villata
    • 1
  1. 1.Université Côte d’Azur, CNRS, Inria, I3SNiceFrance
  2. 2.Fondazione Bruno KesslerTrentoItaly

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