Algorithms for irrelevance-based partial MAPs

Eyal Shlomo Shimony, Bruce D. D'Ambrosio (Editor), Piero P. Bonissone (Editor)

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Irrelevance-based partial MAPs are useful constructs for domain-independent explanation using belief networks. We look at two definitions for such partial MAPs, and prove important properties that are useful in designing algorithms for computing them effectively. We make use of these properties in modifying our standard MAP best-first algorithm, so as to handle irrelevance-based partial MAPs.
Original languageEnglish
Title of host publicationUncertainty Proceedings 1991 Proceedings of the Seventh Conference (1991)
PublisherElsevier
Pages370-377
ISBN (Print)978-1-55860-203-8
DOIs
StatePublished - 1991
EventSeventh Conference on Uncertainty in Artificial Intelligence - University of California at Los Angeles (UCLA), Los Angeles, United States
Duration: 13 Jul 199115 Jul 1991

Conference

ConferenceSeventh Conference on Uncertainty in Artificial Intelligence
Country/TerritoryUnited States
CityLos Angeles
Period13/07/9115/07/91

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