Quantile-constrained Choquet-Wasserstein p-box approximation of arbitrary belief functions

This paper considers the problem of approximating an arbitrary belief function in Dempster-Shafer theory, seen as the imprecise distribution of a random variable with finite range, with a suitable p-box. The quoted p-box is asked to minimize a Choquet-Wasserstein pseudo-distance while satisfying ine...

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Bibliographic Details
Published inIEEE International Fuzzy Systems conference proceedings pp. 1 - 6
Main Authors Cinfrignini, Andrea, Lorenzini, Silvia, Petturiti, Davide, Vantaggi, Barbara
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.07.2025
Subjects
approximation
Approximation algorithms
belief function
Choquet-Wasserstein pseudo-distance
Computational efficiency
Evidence theory
Fuzzy systems
p-box
quantile constraint
Random variables
Upper bound
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ISSN1558-4739
DOI10.1109/FUZZ62266.2025.11152073

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Summary:This paper considers the problem of approximating an arbitrary belief function in Dempster-Shafer theory, seen as the imprecise distribution of a random variable with finite range, with a suitable p-box. The quoted p-box is asked to minimize a Choquet-Wasserstein pseudo-distance while satisfying inequality constraints on the corresponding lower/upper quantile function. We show that the computation of the approximating p-box can be carried out efficiently through a generalization of the Dykstra's algorithm by relying on a proper entropic formulation.
ISSN:1558-4739
DOI:10.1109/FUZZ62266.2025.11152073