Decentralized Control of Partially Observable Markov Decision Processes using Belief Space Macro-actions
IEEE International Conference on Robotics and Automation, 2015.
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 intractable for large problems. To allow f...More
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