Decentralized Control of Partially Observable Markov Decision Processes using Belief Space Macro-actions
IEEE International Conference on Robotics and Automation, 2015.
EI WOS
Abstract:
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
Code:
Data:
Full Text
Tags
Comments