The inferential complexity of bayesian and credal networks

Cassio Polpo de Campos, Fabio Gagliardi Cozman

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureHoofdstukAcademicpeer review

59 Citaten (Scopus)

Samenvatting

This paper presents new results on the complexity of graph-theoretical models that represent probabilities (Bayesian networks) and that represent interval and set valued probabilities (credal networks). We define a new class of networks with bounded width, and introduce a new decision problem for Bayesian networks, the maximin a posteriori. We present new links between the Bayesian and credal networks, and present new results both for Bayesian networks (most probable explanation with observations, maximin a posteriori) and for credal networks (bounds on probabilities a posteriori, most probable explanation with and without observations, maximum a posteriori).

Originele taal-2Engels
TitelInternational Joint Conference on Artificial Intelligence (IJCAI)
Pagina's1313-1318
Aantal pagina's6
StatusGepubliceerd - 1 dec. 2005
Extern gepubliceerdJa
Evenement19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, Verenigd Koninkrijk
Duur: 30 jul. 20055 aug. 2005

Publicatie series

NaamIJCAI International Joint Conference on Artificial Intelligence
ISSN van geprinte versie1045-0823

Congres

Congres19th International Joint Conference on Artificial Intelligence, IJCAI 2005
Land/RegioVerenigd Koninkrijk
StadEdinburgh
Periode30/07/055/08/05

Bibliografische nota

(oral presentation, double-blind peer reviewed by >3 reviewers)

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