31 citations · 86 across the 21 of their papers we have counts for
3 papers · 1 filter
Efficient Reinforcement Learning Development with RLzoo
Zihan Ding, Tianyang Yu, Yanhua Huang +5
Many researchers and developers are exploring for adopting Deep Reinforcement Learning (DRL) techniques in their applications. They however often find such an adoption challenging.…
Crossing The Gap: A Deep Dive into Zero-Shot Sim-to-Real Transfer for Dynamics
Eugene Valassakis, Zihan Ding, Edward Johns
Zero-shot sim-to-real transfer of tasks with complex dynamics is a highly challenging and unsolved problem. A number of solutions have been proposed in recent years, but we have fo…
Sim-to-Real Transfer for Optical Tactile Sensing
Zihan Ding, Nathan F. Lepora, Edward Johns
Deep learning and reinforcement learning methods have been shown to enable learning of flexible and complex robot controllers. However, the reliance on large amounts of training da…