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On the impact of configuration on abstract argumentation automated reasoning

Cerutti, Federico, Vallati, Mauro and Giacomin, Massimiliano 2018. On the impact of configuration on abstract argumentation automated reasoning. International Journal of Approximate Reasoning 92 , pp. 120-138. 10.1016/j.ijar.2017.10.002

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Abstract

In this paper we consider the impact of configuration of abstract argumentation reasoners both when using a single solver and choosing combinations of framework representation–solver options; and also when composing portfolios of algorithms. To exemplify the impact of the framework–solver configuration we consider one of the most configurable solvers, namely ArgSemSAT—runner-up of the last competition on computational models of argumentation (ICCMA-15)—for enumerating preferred extensions. We discuss how to configure the representation of the argumentation framework in the input file and show how this coupled framework–solver configuration can have a remarkable impact on performance. As to the impact of configuring differently structured portfolios of abstract argumentation solvers, we consider the solvers submitted to ICCMA-15, which provided the community with a heterogeneous panorama of approaches for handling abstract argumentation frameworks. A superficial reading of the results of ICCMA-15 is that reduction-based systems (either SAT-based or ASP-based) are always the most efficient. Our investigation, concerning the enumeration of stable and preferred extensions, shows that this is not true in full generality and suggests the areas where the relatively under-developed non reduction-based systems should focus more to improve their performance. Moreover, it also highlights that the state-of-the-art solvers are very complementary and can be successfully combined in portfolios.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Advanced Research Computing @ Cardiff (ARCCA)
Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: Elsevier
ISSN: 0888-613X
Date of First Compliant Deposit: 24 October 2017
Date of Acceptance: 4 October 2017
Last Modified: 09 Oct 2018 06:03
URI: http://orca.cf.ac.uk/id/eprint/105175

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