The inferential complexity of bayesian and credal networks

Cassio Polpo De Campos, Fabio Gagliardi Cozman

Research output: Contribution to conferenceConference Paper

61 Scopus citations

Abstract

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).
Original languageAmerican English
Pages1313-1318
Number of pages6
StatePublished - 1 Dec 2005
Externally publishedYes
EventIJCAI International Joint Conference on Artificial Intelligence -
Duration: 1 Dec 2005 → …

Conference

ConferenceIJCAI International Joint Conference on Artificial Intelligence
Period1/12/05 → …

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