[讲义] reinforcement_q_learning.py

说明：关于强化学习dqn的相关代码，适合初学者认识和了解强化学习dqn
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[讲义] neural_style_tutorial.py

说明：关于风格迁移的相关代码，适合初学者认识和了解风格迁移
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[讲义] saving_loading_models.py

说明：关于保存和加载网络模型的相关代码，适合初学者任何和了解网络模型
<m0_37384317> 上传 | 大小：17kb

[讲义] double_deep_reinforcement_learning.pdf

说明：关于dqn的原始论文，适合初学者对深度强化学习double dqn的认识和了解
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[讲义] dueldqn.pdf

说明：关于duelingdqn的原始论文，适合初学者对深度强化学习duelingdqn的认识和了解Dueling Network Architectures for Deep Reinforcement Learning et al.(2016). The results of Schaul et al.(2016) are the 2.1. Deep Q-networks current published state-of-the-art The value functions as descri
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[讲义] Noisy Networks for Exploration.pdf

说明：关于Noisy Networks for Exploration dqn的原始论文，适合初学者对深度强化学习Noisy Networks for Exploration dqn的认识和了解Published as a conference paper at ICLR 2018 T is assessed by the action-value function Q defined as Q"(.a)=配 ∑ rR(t, at) (1) where E is the expectation ove
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[讲义] Rainbow dqn.pdf

说明：关于Rainbow dqn的原始论文，适合初学者对深度强化学习Rainbow dqn的认识和了解
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[讲义] HIGH-DIMENSIONAL CONTINUOUS CONTROL USING GENERALIZED ADVANTAGE ESTIMATION.pdf

说明：HIGH-DIMENSIONAL CONTINUOUS CONTROL USING GENERALIZED ADVANTAGE ESTIMATIONPublished as a conference paper at ICLR 2016 Here, the subscr ipt of e enumerates the variables being integrated over, where states and actions are sampled sequentially from th
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[讲义] Proximal Policy Optimization Algorithms.pdf

说明：关于Proximal Policy Optimization Algorithms 的原始论文，适合初学者对深度强化学习Proximal Policy Optimization Algorithms 的认识和了解
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[讲义] Sample Efficient Actor-Critic with Experience Replay.pdf

说明：Sample Efficient Actor-Critic with Experience Replay
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[讲义] Continuous control with deep reinforcement learning.pdf

说明：Continuous control with deep reinforcement learning
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[讲义] Addressing Function Approximation Error in Actor-Critic Methods.pdf

说明：Addressing Function Approximation Error in Actor-Critic Methods
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