Quantitative possibility theory and its probabilistic connections

Didier Dubois (1) , Henri Prade (1)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage

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.

Domaines: Intelligence artificielle [cs.AI]

Didier Dubois, Henri Prade. Quantitative possibility theory and its probabilistic connections. Grzegorzewski, Przemyslaw; Hryniewicz, Olgierd; Angeles-Gil, Maria. Soft Methods in Probability, Statistics and Data Analysis, 16, Springer, pp.3--26, 2002, Advances in Intelligent and Soft Computing book series (AINSC), ⟨10.1007/978-3-7908-1773-7_1⟩. ⟨hal-03378847⟩