8 citations · 8 across the 8 of their papers we have counts for
4 papers · 1 filter
Distributional Inverse Reinforcement Learning
Feiyang Wu, Ye Zhao, Anqi Wu
We propose a distributional framework for offline Inverse Reinforcement Learning (IRL) that jointly models uncertainty over reward functions and full distributions of returns. Unli…
SEEC: Stable End-Effector Control with Model-Enhanced Residual Learning for Humanoid Loco-Manipulation
Jaehwi Jang, Zhuoheng Wang, Ziyi Zhou +2
Arm end-effector stabilization is essential for humanoid loco-manipulation tasks, yet it remains challenging due to the high degrees of freedom and inherent dynamic instability of…
RL-augmented Adaptive Model Predictive Control for Bipedal Locomotion over Challenging Terrain
Junnosuke Kamohara, Feiyang Wu, Chinmayee Wamorkar +2
Model predictive control (MPC) has demonstrated effectiveness for humanoid bipedal locomotion; however, its applicability in challenging environments, such as rough and slippery te…
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
Jingyang Ke, Feiyang Wu, Jiyi Wang +2
Traditional approaches to studying decision-making in neuroscience focus on simplified behavioral tasks where animals perform repetitive, stereotyped actions to receive explicit re…