Zhengyu Gan

Faithful Dynamic Imitation Learning from Human Intervention with Dynamic Regret Minimization

Human-in-the-loop (HIL) imitation learning enables agents to learn complex behaviors safely through real-time human intervention. However, existing methods struggle to efficiently leverage agent-generated data due to dynamically evolving trajectory distributions and imperfections caused by human int…