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arXiv:1507.06689cs.AI

Improved Answer-Set Programming Encodings for Abstract Argumentation

Sarah A. Gaggl, Norbert Manthey, Alessandro Ronca, Johannes P. Wallner, Stefan Woltran

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Abstract

The design of efficient solutions for abstract argumentation problems is a crucial step towards advanced argumentation systems. One of the most prominent approaches in the literature is to use Answer-Set Programming (ASP) for this endeavor. In this paper, we present new encodings for three prominent argumentation semantics using the concept of conditional literals in disjunctions as provided by the ASP-system clingo. Our new encodings are not only more succinct than previous versions, but also outperform them on standard benchmarks.

arXiv comments
To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 2015
Journal reference
Theory and Practice of Logic Programming 15 (2015) 434-448
DOI
doi:10.1017/S1471068415000149
Subjects
cs.AIArtificial Intelligence

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