UMR CNRS 7253

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 Description: This course presents the main formalisms for uncertainty representation with emphasis on the theory of belief functions, which generalizes both probability theory and the set-membership approach (including interval analysis). Numerous examples taken from different domains (Artificial Intelligence, multi-sensor fusion, numerical modeling) will illustrate the theoretical notions. Description: This course presents the main formalisms for uncertainty representation with emphasis on the theory of belief functions, which generalizes both probability theory and the set-membership approach (including interval analysis). Numerous examples taken from different domains (Artificial Intelligence, multi-sensor fusion, numerical modeling) will illustrate the theoretical notions.
  
-**Programme (Fall 2013)**+**Program (Fall 2013)**
  
   - 11 September: Introduction to uncertainty {{en:sci22_uncertainty.pdf|lecture notes}}   - 11 September: Introduction to uncertainty {{en:sci22_uncertainty.pdf|lecture notes}}

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en/sci22.txt · Last modified: 2014/09/12 11:29 by tdenoeux
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