Inference in Credal Networks Through Integer Programming

C. P. de Campos, F. G. Cozman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)


A credal network associates a directed acyclic graph with a collection of sets of probability measures; it offers a compact representation for sets of multivariate distributions. In this paper we present a new algorithm for inference in credal networks based on an integer programming reformulation. We are concerned with computation of lower/upper probabilities for a variable in a given credal network. Experiments reported in this paper indicate that this new algorithm has better performance than existing ones for some important classes of networks.
Original languageEnglish
Title of host publicationInternational Symposium on Imprecise Probability: Theories and Applications (ISIPTA)
Number of pages10
Publication statusPublished - 2007

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


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