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improved answer-set programming encoding

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Improved Answer-Set Programming Encodings for Abstract Argumentation

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

arXiv.org Artificial IntelligenceOct-20-2015

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.

improved answer-set programming encoding, logic & formal reasoning, natural language, (16 more...)

arXiv.org Artificial Intelligence

doi: 10.1017/S1471068415000149

1507.06689

Country:

Europe > Germany > Saxony > Dresden (0.04)
Europe > Finland > Uusimaa > Helsinki (0.04)
Europe > Austria > Vienna (0.04)

Genre: Research Report (0.64)

Technology:

Information Technology > Artificial Intelligence > Representation & Reasoning > Logic & Formal Reasoning (1.00)
Information Technology > Artificial Intelligence > Natural Language > Explanation & Argumentation (1.00)

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