Decentralized control of Partially Observable Markov Decision Processes using belief space macro-actions

Decentralized control of Partially Observable Markov Decision Processes using belief space macro-actions

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The focus of this paper is on solving multi-robot planning problems in continuous spaces with partial observability. Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) are general models for multi-robot coordination problems, but representing and solving Dec-POMDPs is often in...

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Bibliographic Details
Main Authors: Omidshafiei, Shayegan, Aghamohammadi, Aliakbar, Amato, Christopher, How, Jonathan P
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Published: Institute of Electrical and Electronics Engineers (IEEE) 2018
Online Access:http://hdl.handle.net/1721.1/116391
https://orcid.org/0000-0003-0903-0137
https://orcid.org/0000-0002-6786-7384
https://orcid.org/0000-0001-8576-1930

Internet

http://hdl.handle.net/1721.1/116391
https://orcid.org/0000-0003-0903-0137
https://orcid.org/0000-0002-6786-7384
https://orcid.org/0000-0001-8576-1930

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