Cerutti, Federico, Tachmazidis, Ilias, Vallati, Mauro, Batsakis, Sotiris, Giacomin, Massimiliano and Antoniou, Grigoris (2015) Exploiting Parallelism for Hard Problems in Abstract Argumentation. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence. AAAI Press, pp. 1475-1481. ISBN 978-1-57735-698-1

Abstract argumentation framework (AF) is a unifying framework able to encompass a variety of nonmonotonic reasoning approaches, logic programming and computational argumentation. Yet, efficient approaches for most of the decision and enumeration problems associated to AF s are missing, thus potentially limiting the efficacy of argumentation-based approaches in real domains. In this paper, we present an algorithm for enumerating the preferred extensions of abstract argumentation frameworks which exploits parallel computation. To this purpose, the SCC-recursive semantics definition schema is adopted, where extensions are defined at the level of specific sub-frameworks. The algorithm shows significant performance improvements in large frameworks, in terms of number of solutions found and speedup.

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