  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.
