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In this paper, we proposed a new stochastic local search algorithm Inc-CCAEP for computing the preferred extensions in (abstract) argumentation frameworks (AF). Inc-CCAEP realizes an incremental version of Swcca, specially designed for computing the preferred extensions in AF. Experiments show that, Inc-CCAEP notably outperforms the state-of-the-art solvers consistently on random benchmarks with non-empty preferred extensions.
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