most citedReward-Adaptive Reinforcement Learning: Dynamic Policy Gradient Optimization for Bipedal Locomotion

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

cs.RO2021★ 2 cited

Reward-Adaptive Reinforcement Learning: Dynamic Policy Gradient Optimization for Bipedal Locomotion

Changxin Huang, Guangrun Wang, Zhibo Zhou +2

Controlling a non-statically bipedal robot is challenging due to the complex dynamics and multi-criterion optimization involved. Recent works have demonstrated the effectiveness of…