Zhang, DongGatica-Perez, DanielBengio, SamyRoy, Deb2006-03-102006-03-102006-03-102005https://infoscience.epfl.ch/handle/20.500.14299/228607We 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.visionzhangtext::conference output::conference proceedings::conference paper