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}, |
| Keywords: | |
| Projects: |
Idiap |
| Authors: | |
| Crossref by |
zhang-rr-05-48b |
| Added by: | [UNK] |
| Total mark: | 0 |
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