On possibilistic and probabilistic approximations of unrestricted belief functions based on the concept of fuzzy t-preorder

Authors:
Enric Hernandez;Jordi Recasens
Affiliations:
Secció de Matemàtiques i Informàtica, ETSAB. Avda. Diagonal, 649 08028, Barcelona, Spain Universitat Politècnica de Catalunya;Secció de Matemàtiques i Informàtica, ETSAV. Pere Serra 1-15 08190, Sant Cugat, Spain Universitat Politècnica de Catalunya
Venue:
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Year:
2002

Citing 6
Cited 2

A computationally efficient approximation of Dempster-Shafer theory

International Journal of Man-Machine Studies
Consonant approximation of belief functions

International Journal of Approximate Reasoning
Approximations for efficient computation in the theory of evidence

Artificial Intelligence
Fuzzy sets as a basis for a theory of possibility

Fuzzy Sets and Systems
Uncertainty-Based Information: Elements of Generalized Information Theory

Uncertainty-Based Information: Elements of Generalized Information Theory
Faithful approximations of belief functions

UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence

Normalizing possibility distributions using t-norms

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
An uncertainty interchange format with imprecise probabilities

International Journal of Approximate Reasoning

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a new method for approximating an unrestricted belief measure assuring that the "order" defined by the compatibility degree between evidence and the singletons set is preserved. Our approach, based on the concept of fuzzy T-preorder, also allows us to define several equivalence criteria over the set of all basic probability assignment functions on a given domain. Some others related aspects as uniqueness of the approximations are also addressed.