Probability-possibility transformations: Application to credal networks

Salem Benferhat, Amelie Levray, Karim Tabia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

This paper deals with belief graphical models and probability-possibility transformations. It first analyzes some properties of transforming a credal network into a possibilistic one. In particular, we are interested in satisfying some properties of probability possibility transformations like dominance and order preservation. The second part of the paper deals with using probability possibility transformations in order to perform MAP inference in credal networks. This problem is known for its high computational complexity in comparison with MAP inference in Bayesian and possibilistic networks. The paper provides preliminary experimental results comparing our approach with both exact and approximate inference in credal networks.
Original languageEnglish
Title of host publicationProceedings of the 9th International Conference on Scalable Uncertainty Management (SUM’15), 2015.
Place of PublicationQuebec, Canada
Number of pages14
Publication statusPublished - 2015
Event9th International Conference on Scalable Uncertainty Management - Quebec City, Canada
Duration: 16 Sept 201518 Sept 2015


Conference9th International Conference on Scalable Uncertainty Management
Abbreviated titleSUM 2015
CityQuebec City
Internet address


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