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 [BibTeX] [Marc21]
Learning influence among interacting Markov chains
Type of publication: Idiap-RR
Citation: zhang-rr-05-48
Number: Idiap-RR-48-2005
Year: 2005
Institution: IDIAP
Address: Martigny, Switzerland
Note: Published in NIPS, Dec, 2005
Abstract: We present a model that learns the influence of interacting Markov chains within a team. The proposed model is a dynamic Bayesian network (DBN) with a two-level structure: individual-level and group-level. Individual level models actions of each player, and the group-level models actions of the team as a whole. Experiments on synthetic multi-player games and a multi-party meeting corpus show the effectiveness of the proposed model.
Userfields: ipdinar={2005}, ipdmembership={vision}, language={English},
Projects Idiap
Authors Zhang, Dong
Gatica-Perez, Daniel
Bengio, Samy
Roy, Deb
Crossref by zhang-rr-05-48b
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