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University of New Mexico

Belief functions

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Extended Pcr Rules For Dynamic Frames, Florentin Smarandache, Jean Dezert Jul 2012

Extended Pcr Rules For Dynamic Frames, Florentin Smarandache, Jean Dezert

Branch Mathematics and Statistics Faculty and Staff Publications

In most of classical fusion problems modeled from belief functions, the frame of discernment is considered as static. This means that the set of elements in the frame and the underlying integrity constraints of the frame are fixed forever and they do not change with time. In some applications, like in target tracking for example, the use of such invariant frame is not very appropriate because it can truly change with time. So it is necessary to adapt the Proportional Conflict Redistribution fusion rules (PCR5 and PCR6) for working with dynamical frames. In this paper, we propose an extension of …


Non Bayesian Conditioning And Deconditioning, Jean Dezert, Florentin Smarandache Apr 2010

Non Bayesian Conditioning And Deconditioning, Jean Dezert, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper, we present a Non-Bayesian conditioning rule for belief revision. This rule is truly Non-Bayesian in the sense that it doesn’t satisfy the common adopted principle that when a prior belief is Bayesian, after conditioning by X, Bel(X|X) must be equal to one. Our new conditioning rule for belief revision is based on the proportional conflict redistribution rule of combination developed in DSmT (Dezert-Smarandache Theory) which abandons Bayes’ conditioning principle. Such Non-Bayesian conditioning allows to take into account judiciously the level of conflict between the prior belief available and the conditional evidence. We also introduce the deconditioning problem …