Aggregating Imprecise Probabilistic Knowledge
Authors: Alessio Benavoli and Alessandro Antonucci
Abstract: The problem of aggregating two or more sources of information containing knowledge about a same domain is considered. We propose an aggregation rule for the case where the available information is modeled by coherent lower previsions, corresponding to convex sets of probability mass functions. The consistency between aggregated beliefs and sources of information is discussed. A closed formula, which specializes our rule to a particular class of models, is also derived. Finally, an alternative explanation of Zadeh's paradox is provided.
Details: In Augustin, T., Coolen, F., Moral, S., Troffaes, M.C.M. (Eds.), ISIPTA '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications. SIPTA, pp. 31-40.
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