Exploiting parallelism for hard problems in abstract argumentation

Federico Cerutti, Ilias Tachmazidis, Mauro Vallati, Sotirios Batsakis, Massimiliano Giacomin, Grigoris Antoniou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

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 AFs are missing, thus 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.

LanguageEnglish
Title of host publicationProceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
PublisherAI Access Foundation
Pages1475-1481
Number of pages7
Volume2
ISBN (Electronic)9781577357001
Publication statusPublished - 1 Jun 2015
Event29th AAAI Conference on Artificial Intelligence and the 27th Innovative Applications of Artificial Intelligence Conference 2015 - Austin, United States
Duration: 25 Jan 201530 Jan 2015
Conference number: 27//29
http://www.aaai.org/Conferences/AAAI/aaai15.php (Link to Conference Website)

Conference

Conference29th AAAI Conference on Artificial Intelligence and the 27th Innovative Applications of Artificial Intelligence Conference 2015
Abbreviated titleAAAI 2015//IAAI 2015
CountryUnited States
CityAustin
Period25/01/1530/01/15
Internet address

Fingerprint

Logic programming
Semantics

Cite this

Cerutti, F., Tachmazidis, I., Vallati, M., Batsakis, S., Giacomin, M., & Antoniou, G. (2015). Exploiting parallelism for hard problems in abstract argumentation. In Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 (Vol. 2, pp. 1475-1481). AI Access Foundation.
Cerutti, Federico ; Tachmazidis, Ilias ; Vallati, Mauro ; Batsakis, Sotirios ; Giacomin, Massimiliano ; Antoniou, Grigoris. / Exploiting parallelism for hard problems in abstract argumentation. Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015. Vol. 2 AI Access Foundation, 2015. pp. 1475-1481
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Cerutti, F, Tachmazidis, I, Vallati, M, Batsakis, S, Giacomin, M & Antoniou, G 2015, Exploiting parallelism for hard problems in abstract argumentation. in Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015. vol. 2, AI Access Foundation, pp. 1475-1481, 29th AAAI Conference on Artificial Intelligence and the 27th Innovative Applications of Artificial Intelligence Conference 2015, Austin, United States, 25/01/15.

Exploiting parallelism for hard problems in abstract argumentation. / Cerutti, Federico; Tachmazidis, Ilias; Vallati, Mauro; Batsakis, Sotirios; Giacomin, Massimiliano; Antoniou, Grigoris.

Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015. Vol. 2 AI Access Foundation, 2015. p. 1475-1481.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Cerutti F, Tachmazidis I, Vallati M, Batsakis S, Giacomin M, Antoniou G. Exploiting parallelism for hard problems in abstract argumentation. In Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015. Vol. 2. AI Access Foundation. 2015. p. 1475-1481