REPORT zhang-rr-05-48/IDIAP Learning influence among interacting Markov chains Zhang, Dong Gatica-Perez, Daniel Bengio, Samy Roy, Deb EXTERNAL http://publications.idiap.ch/attachments/reports/2005/rr-05-48.pdf PUBLIC Idiap-RR-48-2005 2005 IDIAP Martigny, Switzerland Published in NIPS, Dec, 2005 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.