Curricular Subgoals for Inverse Reinforcement Learning

1 code implementation • 14 Jun 2023 • Shunyu Liu, Yunpeng Qing, Shuqi Xu, Hongyan Wu, Jiangtao Zhang, Jingyuan Cong, Tianhao Chen, YunFu Liu, Mingli Song

Inverse Reinforcement Learning (IRL) aims to reconstruct the reward function from expert demonstrations to facilitate policy learning, and has demonstrated its remarkable success in imitation learning.

Autonomous Driving D4RL +2