Shangtong Zhang

Nov 20, 2024 | arxiv.org | Zixuan Xie |Xinyu Liu |Shangtong Zhang

Sep 18, 2024 | arxiv.org | Shangtong Zhang

Aug 2, 2023 | arxiv.org | Shangtong Zhang

Off-policy learning enables a reinforcement learning (RL) agent to reason counterfactually about policies that are not executed and is one of the most important ideas in RL. It, however, can lead to instability when combined with function approximation and bootstrapping, two arguably indispensable ingredients for large-scale reinforcement learning.