Jinming Ma

Improving Offline Reinforcement Learning with Inaccurate Simulators

2024 · arXiv (Cornell University)

Offline reinforcement learning (RL) provides a promising approach to avoid costly online interaction with the real environment. However, the performance of offline RL highly depends on the quality of the datasets, which may cause extrapolation …