AIJul 23, 2015

Improved Answer-Set Programming Encodings for Abstract Argumentation

arXiv:1507.06689v25 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the need for efficient argumentation systems, but it is incremental as it improves existing ASP-based methods.

The paper tackled the problem of designing efficient solutions for abstract argumentation by presenting new Answer-Set Programming encodings for three argumentation semantics, resulting in more succinct and better-performing encodings on standard benchmarks.

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.

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