Non-Destructive Sample Generation From Conditional Belief Functions

Published 25 May 2020 in cs.AI | (2005.11963v1)

Abstract: This paper presents a new approach to generate samples from conditional belief functions for a restricted but non trivial subset of conditional belief functions. It assumes the factorization (decomposition) of a belief function along a bayesian network structure. It applies general conditional belief functions.

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Mieczysław A. Kłopotek

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