Cerutti, Federico, Vallati, Mauro and Giacomin, Massimiliano (2017) An Efficient Java-Based Solver for Abstract Argumentation Frameworks: jArgSemSAT. International Journal on Artificial Intelligence Tools, 26 (2). ISSN 0218-2130

Dung’s argumentation frameworks are adopted in a variety of applications, from
argument-mining, to intelligence analysis and legal reasoning. Despite this broad spectrum
of already existing applications, the mostly adopted solver—in virtue of its
simplicity—is far from being comparable to the current state-of-the-art solvers. On the
other hand, most of the current state-of-the-art solvers are far too complicated to be
deployed in real-world settings. In this paper we provide and extensive description of
jArgSemSAT, a Java re-implementation of ArgSemSAT. ArgSemSAT represents the best
single solver for argumentation semantics with the highest level of computational complexity.
We show that jArgSemSAT can be easily integrated in existing argumentation
systems (1) as an off-the-shelf, standalone, library; (2) as a Tweety compatible library;
and (3) as a fast and robust web service freely available on the Web. Our large experimental
analysis shows that—despite being written in Java—jArgSemSAT would have
scored in most of the cases among the three bests solvers for the two semantics with
highest computational complexity—Stable and Preferred—in the last competition on
computational models of argumentation.

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