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- W2262675902 abstract "Probabilistic abstract argumentation is an extension of Dung's abstract argumentation framework with probability theory. In this setting, we address the problem of computing the probability Pr sem ( S ) that a set S of arguments is an extension according to a semantics sem . We focus on four popular semantics (i.e., complete , grounded , preferred and ideal-set ) for which the state-of-the-art approach is that of estimating Pr sem ( S ) by using a Monte-Carlo simulation technique, as computing Pr sem ( S ) has been proved to be intractable. In this paper, we propose a new Monte-Carlo simulation approach which exploits some properties of the above-mentioned semantics for estimating Pr sem ( S ) using much fewer samples than the state-of-the-art approach, resulting in a significantly more efficient estimation technique. • A new Monte-Carlo-based technique for estimating the probability that a set of arguments is an extension is proposed. • The performances of the proposed technique are thoroughly analyzed both experimentally and theoretically. • The proposed technique outperforms the state of the art." @default.
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- W2262675902 date "2016-02-01" @default.
- W2262675902 modified "2023-10-16" @default.
- W2262675902 title "On efficiently estimating the probability of extensions in abstract argumentation frameworks" @default.
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- W2262675902 doi "https://doi.org/10.1016/j.ijar.2015.11.009" @default.
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