ACDER: Augmented Curiosity-Driven Experience Replay
Boyao Li,Tao Lu,Jiayi Li,Ning Lu,Yinghao Cai,Shuo Wang,Boyao Li,Tao Lu,Jiayi Li,Ning Lu,Yinghao Cai,Shuo Wang
Exploration in environments with sparse feed-back remains a challenging research problem in reinforcement learning (RL). When the RL agent explores the environment randomly, it results in low exploration efficiency, especially in robotic manipulation tasks with high dimensional continuous state and action space. In this paper, we propose a novel method, called Augmented Curiosity-Driven Experience...
