Statistically Efficient Advantage Learning for Offline Reinforcement Learning in Infinite Horizons
无限期离线强化学习中的统计高效优势学习
We consider reinforcement learning (RL) methods in offline domains without additional online data collection, such as mobile health applications. Most of existing policy optimization algorithms in the computer science literature are developed in online settings where data are easy to collect or simulate. Their generalizations to mobile health applications with a pre-collected offline dataset remain are less explored. The aim of this article is to develop a novel advantage…