On the Dempster-Shafer framework and new combination rules
Information Sciences: an International Journal
Consonant approximation of belief functions
International Journal of Approximate Reasoning
Measures of discord in the Dempster-Shafer theory
Information Sciences: an International Journal
On transformations of belief functions to probabilities: Research Articles
International Journal of Intelligent Systems - Uncertainty Processing
Belief models: An order-theoretic investigation
Annals of Mathematics and Artificial Intelligence
Fusion rules for merging uncertain information
Information Fusion
Analyzing the degree of conflict among belief functions
Artificial Intelligence
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
A Geometric Approach to the Theory of Evidence
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Two New Bayesian Approximations of Belief Functions Based on Convex Geometry
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In this paper we study the class of consistent belief functions, as counterparts of consistent knowledge bases in classical logic. We prove that such class can be defined univocally no matter our definition of proposition implied by a belief function. As consistency can be desirable in decision making, the problem of mapping an arbitrary belief function to a consistent one arises, and can be posed in a geometric setup. We analyze here all the consistent transformations induced by minimizing Lp distances between belief functions, represented by the vectors of their basic probabilities.