Abstract
An extension of a set of marginals (small-dimensional distributions) is a joint probability distribution that is a ”good” representative of the knowledge (about the problem area) contained in the marginals. ”Good” means with respect to the subsequent decision-making for which the extension is needed. In the context of probabilistic expert systems, constructing the extension from the marginals may be referred to as the knowledge integration [4], reconstructability analysis [9] or marginal problem. The paper surveys different types of known extensions and on the basis of underlying principles and considerations, new types of extensions — the EEV-centroid and the weighted centroid are suggested.
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© 1993 Springer-Verlag Berlin Heidelberg
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Kříž, O. (1993). On extensions of marginals for decision-making. In: Clarke, M., Kruse, R., Moral, S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1993. Lecture Notes in Computer Science, vol 747. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028202
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DOI: https://doi.org/10.1007/BFb0028202
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