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ECAI 2012

A Probabilistic Semantics for abstract Argumentation

Conference Paper ECAI Long Papers Artificial Intelligence

Abstract

Classical semantics for abstract argumentation frameworks are usually defined in terms of extensions or, more recently, labelings. That is, an argument is either regarded as accepted with respect to a labeling or not. In order to reason with a specific semantics one takes either a credulous or skeptical approach, i. e. an argument is ultimately accepted, if it is accepted in one or all labelings, respectively. In this paper, we propose a more general approach for a semantics that allows for a more fine-grained differentiation between those two extreme views on reasoning. In particular, we propose a probabilistic semantics for abstract argumentation that assigns probabilities or degrees of belief to individual arguments. We show that our semantics generalizes the classical notions of semantics and we point out interesting relationships between concepts from argumentation and probabilistic reasoning. We illustrate the usefulness of our semantics on an example from the medical domain.

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Context

Venue
European Conference on Artificial Intelligence
Archive span
1982-2025
Indexed papers
5223
Paper id
318547152475492297
v2026.09.13