Abstract
Dempster’s aggregation rule plays an important role in the theory of belief functions. Recently, the concept of a generalized credal set has been introduced that allows us to model uncertainty caused by imprecision, conflict and contradiction in information. This concept generalizes in some sense constructions used in evidence theory and imprecise probabilities. In this paper, we show that Dempster’s rule can be viewed as the average conditional of a given plausibility function w.r.t. a random set. This allows us to define the extension of this rule into a wider family of uncertainty models presented by generalized credal sets.
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Bronevich, A.G., Rozenberg, I.N. (2022). The Extension of Dempster’s Combination Rule Based on Generalized Credal Sets. In: Le Hégarat-Mascle, S., Bloch, I., Aldea, E. (eds) Belief Functions: Theory and Applications. BELIEF 2022. Lecture Notes in Computer Science(), vol 13506. Springer, Cham. https://doi.org/10.1007/978-3-031-17801-6_23
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DOI: https://doi.org/10.1007/978-3-031-17801-6_23
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