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On Probabilistic Logical Argumentation
Pilar Dellunde, Lluís Godo, Amanda Vidal
7 - 16
10.3233/FAIA210111
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 339: Artificial Intelligence Research and Development
Abstract

In this paper, we introduce a framework for probabilistic logic-based argumentation inspired on the DeLP formalism and an extensive use of conditional probability. We define probabilistic arguments built from possibly inconsistent probabilistic knowledge bases and study the notions of attack, defeat and preference between these arguments. Finally, we discuss consistency properties of admissible extensions of the Dung’s abstract argumentation graphs obtained from sets of probabilistic arguments and the attack relations between them.

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