Abstract
Abstract argumentation is nowadays a vivid field within artificial intelligence and has seen different developments recently. In particular, enrichments of the standard Dung frameworks have been proposed in order to model scenarios where probabilities or uncertain information have to be expressed. As for standard approaches of abstract argumentation, a uniform logical formalization for such frameworks is of great help in order to understand and compare different approaches. In this paper, we take a first step in this direction and characterize different semantics from the approach of Li et al in terms of probabilistic logic. This not only provides a uniform logical formalization but also might pave the way for future implementations.
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Doder, D., Woltran, S. (2014). Probabilistic Argumentation Frameworks – A Logical Approach. In: Straccia, U., Calì, A. (eds) Scalable Uncertainty Management. SUM 2014. Lecture Notes in Computer Science(), vol 8720. Springer, Cham. https://doi.org/10.1007/978-3-319-11508-5_12
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DOI: https://doi.org/10.1007/978-3-319-11508-5_12
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