Planning for decentralized control of multiple robots under uncertainty

Planning for decentralized control of multiple robots under uncertainty

This paper presents a probabilistic framework for synthesizing control policies for general multi-robot systems that is based on decentralized partially observable Markov decision processes (Dec-POMDPs). Dec-POMDPs are a general model of decision-making where a team of agents must cooperate to optim...

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Bibliographic Details
Main Authors: Amato, Christopher (Contributor), Cruz, Gabriel (Contributor), Maynor, Christopher A. (Contributor), How, Jonathan P. (Contributor), Kaelbling, Leslie P. (Contributor), Konidaris, George D. (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2015-12-28T00:00:56Z.
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