Guided Incremental Construction of Belief Networks

Charles A. Sutton, Brendan Burns, Clayton Morrison, Paul R. Cohen

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

Abstract

Because uncertain reasoning is often intractable, it is hard to reason with a large amount of knowledge. One solution to this problem is to specify a set of possible models, some simple and some complex, and choose which to use based on the problem. We present an architecture for interpreting temporal data, called AIID, that incrementally constructs belief networks based on data that arrives asynchronously. It synthesizes the opportunistic control of the blackboard architecture with recent work on constructing belief networks from fragments. We have implemented this architecture in the domain of military analysis.
Original languageEnglish
Title of host publicationAdvances in Intelligent Data Analysis V
Subtitle of host publication5th International Symposium on Intelligent Data Analysis, IDA 2003, Berlin, Germany, August 28-30, 2003. Proceedings
EditorsMichael R. Berthold, Hans-Joachim Lenz, Elizabeth Bradley, Rudolf Kruse, Christian Borgelt
PublisherSpringer-Verlag GmbH
Pages533-543
Number of pages11
ISBN (Electronic)978-3-540-45231-7
ISBN (Print)978-3-540-40813-0
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Volume2810
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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