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Titlebook: Scalable Uncertainty Management; 12th International Davide Ciucci,Gabriella Pasi,Barbara Vantaggi Conference proceedings 2018 Springer Na

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Explaining the Most Probable Explanationplanations of the MPE solution in natural language to make it more understandable for the domain expert. Moreover, the approach allows decision makers to further explore explanations of different scenarios providing more insight why certain alternative explanations are considered less probable than the MPE solution.
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On Instantiating Generalised Properties of Gradual Argumentation Frameworksn proposed. In this paper we show how this generalised parametric formulation enables the identification of new properties not previously considered in the literature and discuss their usefulness to capture alternative requirements coming from different application contexts.
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A Credal Extension of Independent Choice Logiccannot be assumed, and a specific dependence model cannot be assessed. Preliminary tests on an object ranking application show that, despite the loose underlying assumptions, informative inferences can be extracted.
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Distribution-Aware Sampling of Answer Setsabilistically weighted facts and rules as constraints for an approximate sampling task with specifiable accuracy. At this, we do not impose any independence requirements on random variables. An experimental evaluation investigates the performance characteristics of the presented algorithms.
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0302-9743 proaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models..978-3-030-00460-6978-3-030-00461-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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