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...
Main Authors: | Ure, N. Kemal, Chowdhary, Girish, Chen, Yu Fan, How, Jonathan P., Vian, John |
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Other Authors: | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
Format: | Article |
Language: | English |
Published: |
Springer Netherlands
2016
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Online Access: | http://hdl.handle.net/1721.1/103618 https://orcid.org/0000-0001-8576-1930 https://orcid.org/0000-0003-3756-3256 |
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