Bayesian and non-Bayesian evidential updating
Artificial Intelligence
An inference technique for integrating knowledge from disparate sources
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Robustness analysis of Bayesian networks with local convex sets of distributions
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Partially specified belief functions
UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence
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While every Shafer belief function corresponds to a set of interval beliefs on the atoms of the frame of di$cernment, an arbitrarily specified set of intervals of belief may not correspond to any belief function, even when it does correspond to bounds imposed by sets of probability functions. This paper proves necessary and sufficient conditions which must be met by a set of belief intervals over atoms if a corresponding belief function exists. The sufficiency is proved via an an O(n) algorithm which will always construct an corresponding belief function, if one exits, for a specific set of intervals