2023
Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL
NeurIPS 2023poster
Offline reinforcement learning (RL) offers an appealing approach to real-world tasks by learning policies from pre-collected datasets without interacting with the environment. However, the performance of existing offline RL algorithms heavily depends on the scale and state-action space coverage of d…