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 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.

• Publication year

  2025

• Venue

  IEEE International Conference on Fuzzy Systems

• Publication date

  2025-07-06

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/FUZZ62266.2025.11152073
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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