2 code implementations • 16 Oct 2020 • Jiancong Huang, Juan Rojas, Matthieu Zimmer, Hongmin Wu, Yisheng Guan, Paul Weng
Insufficient learning (due to convergence to local optima) results in under-performing policies whilst redundant learning wastes time and resources.
1 code implementation • 19 Oct 2019 • Yijiong Lin, Jiancong Huang, Matthieu Zimmer, Juan Rojas, Paul Weng
Deep reinforcement learning (DRL) is a promising approach for adaptive robot control, but its current application to robotics is currently hindered by high sample requirements.
1 code implementation • 24 Sep 2019 • Yijiong Lin, Jiancong Huang, Matthieu Zimmer, Yisheng Guan, Juan Rojas, Paul Weng
Our work demonstrates that invariant transformations on RL trajectories are a promising methodology to speed up learning in deep RL.