Knowledge acquisition for goal prediction in a multi-user adventure game

David W Albrecht, Ann E Nicholson, Ingrid Zukerman

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


    We present an approach to goal recognition which uses a Dynamic Belief Network to represent domain features needed to identify users' goals and plans. Different network structures have been developed, and their conditional probability distributions have been automatically acquired from training data. These networks show a high degree of accuracy in predicting users' goals. Our approach allows the use of incomplete, sparse and noisy data during both training and testing. We then apply simple learning techniques to learn significant actions in the domain. This speeds up the performance of the most promising dynamic belief networks without loss in predictive accuracy.
    Original languageEnglish
    Title of host publicationResearch and Development in Knowledge Discovery and Data Mining
    Subtitle of host publicationSecond Pacific-Asia Conference, PAKDD-98 Melbourne, Australia, April 15-17, 1998 Proceedings
    EditorsXindong Wu, Ramamohanarao Kotagiri, Kevin B. Korb
    Place of PublicationBerlin Germany
    Number of pages12
    ISBN (Print)3540643834
    Publication statusPublished - 1998
    EventPacific-Asia Conference on Knowledge Discovery and Data Mining 1998 - Melbourne, Australia
    Duration: 15 Apr 199817 Apr 1998
    Conference number: 2nd (Proceedings)

    Publication series

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


    ConferencePacific-Asia Conference on Knowledge Discovery and Data Mining 1998
    Abbreviated titlePAKDD 1988
    Internet address

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