63 citations · 69 across the 4 of their papers we have counts for
4 papers
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning
Setareh Cohan, Nam Hee Kim, David Rolnick +1
Policies produced by deep reinforcement learning are typically characterised by their learning curves, but they remain poorly understood in many other respects. ReLU-based policies…
Style-ERD: Responsive and Coherent Online Motion Style Transfer
Tianxin Tao, Xiaohang Zhan, Zhongquan Chen +1
Motion style transfer is a common method for enriching character animation. Motion style transfer algorithms are often designed for offline settings where motions are processed in…
A Survey on Reinforcement Learning Methods in Character Animation
Ariel Kwiatkowski, Eduardo Alvarado, Vicky Kalogeiton +4
Reinforcement Learning is an area of Machine Learning focused on how agents can be trained to make sequential decisions, and achieve a particular goal within an arbitrary environme…
Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie
Zhaoming Xie, Patrick Clary, Jeremy Dao +3
Deep reinforcement learning (DRL) is a promising approach for developing legged locomotion skills. However, the iterative design process that is inevitable in practice is poorly su…