Admissibility in Probabilistic Argumentation

نویسندگان

چکیده

Abstract argumentation is a prominent reasoning framework. It comes with variety of semantics and has lately been enhanced by probabilities to enable quantitative treatment argumentation. While admissibility fundamental notion for classical in abstract frameworks, it barely reflected so far the probabilistic setting. In this paper, we address based on notions admissibility. Our approach follows natural idea defining systematically imposing constraints joint probability distribution sets arguments, rather than single arguments. As result, there might be either uniquely defined satisfying constraints, but also none, many, or even an infinite number distributions are possible. We provide corresponding complete stable show how labeling schemes bridge from back argument labelings. relation existing work argumentation, present taxonomy semantic notions. Enabled constraint-based approach, standard problems can tackled SMT solvers, as demonstrate proof-of-concept implementation.

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ژورنال

عنوان ژورنال: Journal of Artificial Intelligence Research

سال: 2022

ISSN: ['1076-9757', '1943-5037']

DOI: https://doi.org/10.1613/jair.1.13530