Properties of measures of information in evidence and possibility theories
Fuzzy Sets and Systems - Special Issue: Measures of Uncertainty
Representation of fuzzy measures through probabilities
Fuzzy Sets and Systems
Partial inconsistency of probability envelopes
Fuzzy Sets and Systems
A comparison of similarity measures of fuzzy values
Fuzzy Sets and Systems
A comparative study of similarity measures
Fuzzy Sets and Systems
Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A. Zadeh
Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A. Zadeh
A non-specificity measure for convex sets of probability distributions
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - special issue on models for imprecise probabilities and partial knowledge
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Maximum of entropy for credal sets
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Upper entropy of credal sets. Applications to credal classification
International Journal of Approximate Reasoning
Information Affinity: A New Similarity Measure for Possibilistic Uncertain Information
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Distances in evidence theory: Comprehensive survey and generalizations
International Journal of Approximate Reasoning
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When there is uncertainty about the values of a variable, it is possible to have different pieces of information about it. This can be due to the fact that they represent the points of view of different agents and these agents have followed different criteria when codify the pieces of information by means of numbers. The aim of this paper is to provide tools for the comparison of these representations. This is done in the framework of imprecise probabilities, more concretely the credal set theory is used. The reason is that credal sets are very general, including as particular cases possibility theory, probability theory and belief functions. So it can serve as basis to compare the representations of information obtained by following these formalisms. The measures used for comparison are: inconsistency measure, inclusion index and informative distance.