Skip to Main content Skip to Navigation
Conference papers

Prejudiced Information Fusion Using Belief Functions

Abstract : G. Shafer views belief functions as the result of the fusion of elementary partially reliable testimonies from different sources. But any belief function cannot be seen as the combination of simple support functions representing such testimonies. Indeed the result of such a combination only yields a special kind of belief functions called separable. In 1995, Ph. Smets has indicated that any belief function can be seen as the combination of so-called generalized simple support functions. We propose a new interpretation of this result in terms of a pair of separable belief functions, one of them modelling testimonies while the other represents the idea of prejudice. The role of the latter is to weaken the weights of the focal sets of the former separable belief function. This bipolar view accounts for a form of resistance to accept the information supplied by the sources, which differs from the discounting of sources.
Keywords : Belief functions
Document type :
Conference papers
Complete list of metadatas

Cited literature [13 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02181920
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Friday, July 12, 2019 - 2:44:29 PM
Last modification on : Thursday, July 2, 2020 - 10:01:51 AM

File

dubois_22565.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02181920, version 1
  • OATAO : 22565

Citation

Didier Dubois, Francis Faux, Henri Prade. Prejudiced Information Fusion Using Belief Functions. International Conference on Belief Functions (BELIEF 2018), Sep 2018, Compiègne, France. pp.77-85. ⟨hal-02181920⟩

Share

Metrics

Record views

67

Files downloads

148