Inference in Credal Networks Through Integer Programming

C. P. de Campos, Fabio Gagliardi Cozman

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

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)
PublisherSIPTA
Pages145-154
Number of pages10
Publication statusPublished - 2007

Fingerprint

Dive into the research topics of 'Inference in Credal Networks Through Integer Programming'. Together they form a unique fingerprint.

Cite this