Abstract
This paper presents a novel SAT-based approach for the computation
of extensions in abstract argumentation, with focus on preferred semantics, and
an empirical evaluation of its performances. The approach is based on the idea
of reducing the problem of computing complete extensions to a SAT problem
and then using a depth-first search method to derive preferred extensions. The
proposed approach has been tested using two distinct SAT solvers and compared
with three state-of-the-art systems for preferred extension computation. It turns
out that the proposed approach delivers significantly better performances in the
large majority of the considered cases.
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