Anytime Intention Recognition via Incremental Bayesian Network Reconstruction

DI Group Author

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

2 Citations (Scopus)


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 languageUnknown
Title of host publicationAAAI Fall Symposium Series
Editors AAAI
Place of Publication
Publication statusPublished - 1 Jan 2010
EventAAAI Fall Symposium Series -
Duration: 1 Jan 2010 → …


ConferenceAAAI Fall Symposium Series
Period1/01/10 → …

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