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[논문 리뷰] Noisy Networks for Exploration (NoisyNet)

[1706.10295] Noisy Networks for Exploration (arxiv.org) Noisy Networks for Exploration We introduce NoisyNet, a deep reinforcement learning agent with parametric noise added to its weights, and show that the induced stochasticity of the agent's policy can be used to aid efficient exploration. The parameters of the noise are learned with grad arxiv.org 이번 논문에는 DQN에 있는 fully connected layer에 param..