Mixed experience sampling for off-policy reinforcement learning

Jiayu Yu, Jingyao Li, Shuai Lü, Shuai Han

Abstract: Highlights•This paper formulates the sampling probability, and analyzes the monotonic influence.•Three optional sampling strategies based on sampling frequency are designed.•A sampling strategy based on similarity is designed.•FSER (ER based on frequency and similarity) algorithm is proposed.•FSER outperforms the state-of-the-art results on multiple tasks.