Anytime intention recognition via incremental bayesian network reconstruction

The Anh Han, Luís Moniz Pereira

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

    2 Citations (Scopus)

    Abstract

    This paper presents an anytime algorithm for incremental intention recognition in a changing world. The algorithm is performed by dynamically constructing the intention recognition model on top of a prior domain knowledge base. The model is occasionally reconfigured by situating itself in the changing world and removing newly found out irrelevant intentions. We also discuss some approaches to knowledge base representation for supporting situation-dependent model construction. Reconfigurable Bayesian Networks are employed to produce the intention recognition model.

    Original languageEnglish
    Title of host publicationProactive Assistant Agents - Papers from the AAAI Fall Symposium, Technical Report
    Pages20-25
    Number of pages6
    VolumeFS-10-07
    Publication statusPublished - 1 Dec 2010
    Event2010 AAAI Fall Symposium - Arlington, VA, United States
    Duration: 11 Nov 201013 Nov 2010

    Conference

    Conference2010 AAAI Fall Symposium
    CountryUnited States
    CityArlington, VA
    Period11/11/1013/11/10

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  • Cite this

    Han, T. A., & Pereira, L. M. (2010). Anytime intention recognition via incremental bayesian network reconstruction. In Proactive Assistant Agents - Papers from the AAAI Fall Symposium, Technical Report (Vol. FS-10-07, pp. 20-25)