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Found 3 papers, 1 papers with code
Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation
Imitation learning is a powerful paradigm for robot skill acquisition.
Probabilistically Safe Policy Transfer
Although learning-based methods have great potential for robotics, one concern is that a robot that updates its parameters might cause large amounts of damage before it learns the optimal policy.
Learning Deep Neural Network Policies with Continuous Memory States
We evaluate our method on tasks involving continuous control in manipulation and navigation settings, and show that our method can learn complex policies that successfully complete a range of tasks that require memory.
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