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Human-Robot Collaboration via Deep Reinforcement Learning of Real-World Interactions
[article]
2019
arXiv
pre-print
We present a robotic setup for real-world testing and evaluation of human-robot and human-human collaborative learning. Leveraging the sample-efficiency of the Soft Actor-Critic algorithm, we have implemented a robotic platform able to learn a non-trivial collaborative task with a human partner, without pre-training in simulation, and using only 30 minutes of real-world interactions. This enables us to study Human-Robot and Human-Human collaborative learning through real-world interactions. We
arXiv:1912.01715v1
fatcat:frotcu6f3vccrbapqmndd6dpee