Distributed Learning for Planning Under Uncertainty Problems with Heterogeneous Teams

This paper considers the problem of multiagent sequential decision making under uncertainty and incomplete knowledge of the state transition model. A distributed learning framework, where each agent learns an individual model and shares the results with the team, is proposed. The challenges associat...

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Bibliographic Details
Main Authors: Ure, N. Kemal (Contributor), Chowdhary, Girish (Author), Chen, Yu Fan (Contributor), How, Jonathan P. (Contributor), Vian, John (Author)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Springer Netherlands, 2016-07-14T21:59:57Z.
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