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.
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The authors would like to acknowledge the use of the University of Huddersfield Queensgate Grid in carrying out this work.
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Vallati, M., Cerutti, F., Giacomin, M. (2017). On the Combination of Argumentation Solvers into Parallel Portfolios. In: Peng, W., Alahakoon, D., Li, X. (eds) AI 2017: Advances in Artificial Intelligence. AI 2017. Lecture Notes in Computer Science(), vol 10400. Springer, Cham. https://doi.org/10.1007/978-3-319-63004-5_25
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DOI: https://doi.org/10.1007/978-3-319-63004-5_25
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