Belief network algorithms: a study of performance based on domain characterisation

Nathalie Jitnah, Ann E Nicholson

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    2 Citations (Scopus)


    In recent years belief networks have become a popular representation for reasoning with incomplete and changing information and are used in a wide variety of applications. There are a number of exact and approximate inference algorithms available for performing belief updating, however in general the task is NP-hard. Typically comparisons are made of only a few algorithms, and on a particular example network. We survey belief network algorithms and propose a system for domain characterisation as a basis for algorithm comparison. We present performance results using this framework from three sets of experiments: (1) on the Likelihood Weighting (LW) and Logic Sampling (LS) stochastic simulation algorithms? (2) on the performance of LW and Jensen's algorithms on state-space abstracted networks, (3) some comparisons of the time performance of LW, LS and the Jensen algorithm. Our results indicate that domain characterisation can be useful for predicting inference algorithm performance on a belief network for a new application domain.
    Original languageEnglish
    Title of host publicationLearning and Reasoning with Complex Representations
    Subtitle of host publicationPRICAI'96 Workshops on Reasoning with Incomplete and Changing Information and on Inducing Complex Representations Cairns, Australia, August 26-30, 1996 Selected Papers
    EditorsGrigoris Antoniou, Aditya K. Ghose, Miroslaw Truszczynski
    Place of PublicationBerlin Germany
    Number of pages20
    ISBN (Print)354064413X
    Publication statusPublished - 1998
    EventPacific Rim International Conference on Artificial Intelligence 1996 - Cairns, Australia
    Duration: 26 Aug 199630 Aug 1996
    Conference number: 4th (Proceedings)

    Publication series

    NameLecture Notes in Computer Science
    ISSN (Print)0302-9743


    ConferencePacific Rim International Conference on Artificial Intelligence 1996
    Abbreviated titlePRICAI 1996
    Internet address

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