Toward a computational analysis of probabilistic argumentation frameworks

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Abstract

In this article we analyze probabilistic argumentation frameworks (PAFs), defined as an extension of Dung abstract argumentation frameworks in which each argument n is asserted with a probability pn. The debate around PAFs has so far centered on their theoretical definition and basic properties. This work contributes to their computational analysis by proposing a first recursive algorithm to compute the probability of acceptance of each argument under grounded and preferred semantics and by studying the behavior of PAFs with respect to reinstatement, cycles, and changes in argument structure. The computational tools proposed may provide strategic information for agents selecting the next step in an open argumentation process and they represent a contribution in the debate about gradualism in abstract argumentation.

Original languageEnglish
Pages (from-to)254-278
Number of pages25
JournalCybernetics and Systems
Volume45
Issue number3
DOIs
Publication statusPublished - 3 Apr 2014

Keywords

  • abstract argumentation
  • argumentation theory
  • grounded and preferred semantics
  • probabilistic reasoning

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