Computing lower and upper expectations under epistemic independence

Cassio Polpo de Campos, Fabio Gagliardi Cozman

Research output: Contribution to journalArticle

23 Citations (Scopus)
202 Downloads (Pure)

Abstract

This paper investigates the computation of lower/upper expectations that must cohere with a collection of probabilistic assessments and a collection of judgements of epistemic independence. New algorithms, based on multilinear programming, are presented, both for independence among events and among random variables. Separation properties of graphical models are also investigated.
Original languageEnglish
Pages (from-to)244-260
Number of pages17
JournalInternational Journal of Approximate Reasoning
Volume44
Issue number3
Early online date26 Sep 2006
DOIs
Publication statusPublished - Mar 2007

Bibliographical note

Reasoning with Imprecise Probabilities

Keywords

  • Multilinear programming

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