Abstract
In this paper we propose PARTY, a Probabilistic Abstract aRgumenTation sYstem that assesses the probability that a set of arguments is an extension according to a semantics. PARTY deals with five popular semantics, i.e., admissible, stable, complete, grounded, and preferred: it implements polynomial algorithms for computing the probability of the extensions for admissible and stable semantics and it implements an efficient Monte-Carlo simulation algorithm for estimating the probability of the extensions for the other semantics, which have been shown to be intractable in [19, 20]. The experimental evaluation shows that PARTY is more efficient than the state-of-the art approaches and that it can be profitable executed on devices having reduced computational resources.
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Fazzinga, B., Flesca, S., Parisi, F., Pietramala, A. (2015). PARTY: A Mobile System for Efficiently Assessing the Probability of Extensions in a Debate. In: Chen, Q., Hameurlain, A., Toumani, F., Wagner, R., Decker, H. (eds) Database and Expert Systems Applications. Globe DEXA 2015 2015. Lecture Notes in Computer Science(), vol 9261. Springer, Cham. https://doi.org/10.1007/978-3-319-22849-5_16
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