1 code implementation • 9 Nov 2020 • M. Tuluhan Akbulut, Utku Bozdogan, Ahmet Tekden, Emre Ugur
For this, the experience of the robot, which can be bootstrapped from demonstrated trajectories, is used to train a novel Neural Processes-based deep network that samples from its latent space and generates the required trajectories given desired rewards.
no code implementations • 25 Mar 2020 • M. Tuluhan Akbulut, Erhan Oztop, M. Yunus Seker, Honghu Xue, Ahmet E. Tekden, Emre Ugur
To equip robots with dexterous skills, an effective approach is to first transfer the desired skill via Learning from Demonstration (LfD), then let the robot improve it by self-exploration via Reinforcement Learning (RL).