Daoming Lyu

Variance-Reduced Off-Policy Memory-Efficient Policy Search

2020 · arXiv (Cornell University)

Off-policy policy optimization is a challenging problem in reinforcement learning (RL). The algorithms designed for this problem often suffer from high variance in their estimators, which results in poor sample efficiency, and have issues with …