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Chapitre D'ouvrage Année : 2020

Representations of Uncertainty in AI: Beyond Probability and Possibility

Résumé

This chapter completes the survey of the existing frameworks for representing uncertain and incomplete information, started in the previous chapter of this volume. The theory of belief functions and the theory of imprecise probabilities are presented. The latter setting is mathematically more general than the former, and both include probability theory and quantitative possibility theory as particular cases. Their respective knowledge representation capabilities are highlighted.
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Dates et versions

hal-02921351 , version 1 (25-08-2020)

Identifiants

Citer

Thierry Denoeux, Didier Dubois, Henri Prade. Representations of Uncertainty in AI: Beyond Probability and Possibility. A Guided Tour of Artificial Intelligence Research (vol. I), Springer International Publishing, pp.119-150, 2020, ⟨10.1007/978-3-030-06164-7_4⟩. ⟨hal-02921351⟩
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