Logan Mondal Bhamidipaty

RENEW: Towards Learning World Models and Repairing Model Exploitation from Preferences

Logan Mondal Bhamidipaty, Mykel Kochenderfer, Subramanian Ramamoorthy

World models are widely used in offline reinforcement learning (RL) to improve sample efficiency and generate experience beyond a fixed dataset. However, they are vulnerable to model exploitation where data coverage is thin. Prior work addresses this either by collecting more exp…Read more