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Quantitative Possibility Theory and its Probabilistic Connections

  • Didier Dubois
  • Henri Prade
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 16)

Abstract

Possibility theory is a representation framework general enough to model various kinds of information items: numbers, intervals, consonant random sets, special kind of probability families, as well as linguistic information, and uncertain formulae in logical settings. This paper focuses on quantitative possibility measures cast in the setting of imprecise probabilities. Recent results on possibility/probability transformations are recalled. The probabilistic interpretation of possibility measures sheds some light on defuzzification methods and suggests a common framework for fuzzy interval analysis and calculations with random parameters.

Keywords

Fuzzy Number Triangular Fuzzy Number Belief Function Possibility Distribution Possibility Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Didier Dubois
    • 1
  • Henri Prade
    • 1
  1. 1.IRIT-CNRSUniversite Paul SabatierToulouseFrance

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