The Combination of Evidence in the Transferable Belief Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perspectives on the theory and practice of belief functions
International Journal of Approximate Reasoning
Artificial Intelligence
Representation of evidence by hints
Advances in the Dempster-Shafer theory of evidence
Constructing the Pignistic Probability Function in a Context of Uncertainty
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Quantifying beliefs by belief functions: an axiomatic justification
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
International Journal of Approximate Reasoning
Reasoning with imprecise belief structures
International Journal of Approximate Reasoning
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We construct the belief function that quantifies the agent' beliefs about which event of Ω will occurred when he knows that the event is selected by a chance set-up and that the probability function associated to the chance set up is only partially known.