Representations of Uncertainty in Artificial Intelligence: Probability and Possibility - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2020

Representations of Uncertainty in Artificial Intelligence: Probability and Possibility

Résumé

Due to its major focus on knowledge representation and reasoning, artificial intelligence was bound to deal with various frameworks for the handling of uncertainty: probability theory, but more recent approaches as well: possibility theory, evidence theory, and imprecise probabilities. The aim of this chapter is to provide an introductive survey that lays bare specific features of two basic frameworks for representing uncertainty: probability theory and possibility theory, while highlighting the main issues that the task of representing uncertainty is faced with. This purpose also provides the opportunity to position related topics, such as rough sets and fuzzy sets, respectively motivated by the need to account for the granularity of representations as induced by the choice of a language, and the gradual nature of natural language predicates. Moreover, this overview includes concise presentations of yet other theoretical representation frameworks such as formal concept analysis, conditional events and ranking functions, and also possibilistic logic, in connection with the uncertainty frameworks addressed here. The next chapter in this volume is devoted to more complex frameworks: belief functions and imprecise probabilities.
Fichier principal
Vignette du fichier
volume-1-chapitre-3-Springer.pdf (302.99 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02921346 , version 1 (25-08-2020)

Identifiants

Citer

Thierry Denoeux, Didier Dubois, Henri Prade. Representations of Uncertainty in Artificial Intelligence: Probability and Possibility. A Guided Tour of Artificial Intelligence Research Volume I: Knowledge Representation, Reasoning and Learning, Springer International Publishing, pp.69-117, 2020, ⟨10.1007/978-3-030-06164-7_3⟩. ⟨hal-02921346⟩
98 Consultations
616 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More