Inferring from Inconsistency in Preference-Based Argumentation Frameworks

Authors:
Leila Amgoud;Claudette Cayrol
Affiliations:
Institut de Recherche en Informatique de Toulouse (I.R.I.T), Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex, France. e-mail: amgoud@irit.fr;Institut de Recherche en Informatique de Toulouse (I.R.I.T), Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex, France. e-mail: ccayrol@irit.fr
Venue:
Journal of Automated Reasoning
Year:
2002

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Abstract

Argumentation is a promising approach to handle inconsistent knowledge bases, based on the justification of plausible conclusions by arguments. Because of inconsistency, however, arguments may be defeated by counterarguments (or defeaters). The problem is thus to select the most acceptable arguments. In this paper we investigate preference-based acceptability. The basic idea is to accept undefeated arguments and also arguments that are preferred to their defeaters. We say that these arguments defend themselves against their defeaters. We define argumentation frameworks based on that preference-based acceptability. Finally, we study associated inference relations for reasoning with inconsistent knowledge bases.