Unsupervised Salient Patch Selection for Data-Efficient Reinforcement Learning

Zhaohui Jiang, Paul Weng

To improve the sample efficiency of vision-based deep reinforcement learning (RL), we propose a novel method, called SPIRL, to automatically extract important patches from input im…