An Optimistic Perspective on Offline Reinforcement Learning
Published in
International Conference on Machine Learning(2019)External Links:
TL
TL;DR
It is demonstrated that recent off-policy deep RL algorithms, even when trained solely on this replay dataset, outperform the fully trained DQN agent and Random Ensemble Mixture (REM), a robust Q-learning algorithm that enforces optimal Bellman consistency on random convex combinations of multiple Q-value estimates is presented.