Skip to Main content Skip to Navigation

Observations probabilistes dans les réseaux bayésiens

Abstract : In a Bayesian network, evidence on a variable usually signifies that this variable is instantiated, meaning that the observer can affirm with certainty that the variable is in the signaled state. This thesis focuses on other types of evidence, often called uncertain evidence, which cannot be represented by the simple assignment of the variables. This thesis clarifies and studies different concepts of uncertain evidence in a Bayesian network and offers various applications of uncertain evidence in Bayesian networks.Firstly, we present a review of uncertain evidence in Bayesian networks in terms of terminology, definition, specification and propagation. It shows that the vocabulary is not clear and that some terms are used to represent different concepts.We identify three types of uncertain evidence in Bayesian networks and we propose the followingterminology: likelihood evidence, fixed probabilistic evidence and not-fixed probabilistic evidence. We define them and describe updating algorithms for the propagation of uncertain evidence. Finally, we propose several examples of the use of fixed probabilistic evidence in Bayesian networks. The first example concerns evidence on a subpopulation applied in the context of a geographical information system. The second example is an organization of agent encapsulated Bayesian networks that have to collaborate together to solve a problem. The third example concerns the transformation of evidence on continuous variables into fixed probabilistic evidence. The algorithm BN-IPFP-1 has been implemented and used on medical data from CHU Habib Bourguiba in Sfax.
Complete list of metadatas

Cited literature [124 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-01193033
Contributor : Abes Star :  Contact
Submitted on : Friday, September 4, 2015 - 10:52:30 AM
Last modification on : Thursday, February 13, 2020 - 10:21:10 AM
Document(s) archivé(s) le : Saturday, December 5, 2015 - 12:12:17 PM

File

Ben_Mrad_Ali2.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-01193033, version 1

Collections

Citation

Ali Ben Mrad. Observations probabilistes dans les réseaux bayésiens. Intelligence artificielle [cs.AI]. Université de Valenciennes et du Hainaut-Cambresis; École nationale d'Ingénieurs de Sfax (Tunisie), 2015. Français. ⟨NNT : 2015VALE0018⟩. ⟨tel-01193033⟩

Share

Metrics

Record views

475

Files downloads

2933