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End-to-end nonprehensile rearrangement with deep reinforcement learning and simulation-to-reality transfer.
Weihao Yuan
Kaiyu Hang
Danica Kragic
Michael Yu Wang
Johannes A. Stork
Published in:
Robotics Auton. Syst. (2019)
Keyphrases
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end to end
reinforcement learning
transfer learning
wireless ad hoc networks
admission control
congestion control
ad hoc networks
multipath
scalable video
motion estimation
application layer
high bandwidth