Abstract
In the light of the increasing interest in efficient algorithms for solving abstract argumentation problems and the pervasive availability of multicore machines, a natural research issue is to combine existing argumentation solvers into parallel portfolios. In this work, we introduce six methodologies for the automatic configuration of parallel portfolios of argumentation solvers for enumerating the preferred extensions of a given framework. In particular, four methodologies aim at combining solvers in static portfolios, while two methodologies are designed for the dynamic configuration of parallel portfolios. Our empirical results demonstrate that the configuration of parallel portfolios is a fruitful way for exploiting multicore machines, and that the presented approaches outperform the state of the art of parallel argumentation solvers.
| Original language | English |
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| Title of host publication | AI 2017: Advances in Artificial Intelligence |
| Subtitle of host publication | 30th Australasian Joint Conference, Melbourne, VIC, Australia, August 19–20, 2017, Proceedings |
| Editors | Wei Peng, Damminda Alahakoon, Xiaodong Li |
| Publisher | Springer Verlag |
| Pages | 315-327 |
| Number of pages | 13 |
| Edition | 1st |
| ISBN (Electronic) | 9783319630045 |
| ISBN (Print) | 9783319630038 |
| DOIs | |
| Publication status | Published - 9 Jul 2017 |
| Event | 30th Australasian Joint Conference on Artificial Intelligence - Melbourne, Australia Duration: 19 Aug 2017 → 20 Aug 2017 Conference number: 30 https://link.springer.com/conference/ausai (Link to Conference Website ) |
Publication series
| Name | Lecture Notes in Artificial Intelligence |
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| Publisher | Springer Verlag |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 30th Australasian Joint Conference on Artificial Intelligence |
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| Abbreviated title | AI'17 |
| Country/Territory | Australia |
| City | Melbourne |
| Period | 19/08/17 → 20/08/17 |
| Internet address |
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