NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning

ICLR 2019 Sirui XieJunning HuangLanxin LeiChunxiao LiuZheng MaWei ZhangLiang Lin

Reinforcement learning agents need exploratory behaviors to escape from local optima. These behaviors may include both immediate dithering perturbation and temporally consistent exploration... (read more)

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