【代碼集合】深度強化學習Pytorch實現集錦

本次分享的是用PyTorch語言編寫的深度強化學習演算法的高質量實現

，

這些IPython筆記本的目的主要是幫助練習和理解這些論文；因此，在某些情況下，我將選擇可讀性而不是效率。首先，我會上傳論文的實現，然後是標記來解釋代碼的每一部分。

相關論文

1. 
   

   Human Level Control Through Deep Reinforement Learning

    

   [Publication] 

   https://deepmind.com/research/publications/human-level-control-through-deep-reinforcement-learning/

   
   

    

   [code]

    https://github.com/qfettes/DeepRL-Tutorials/blob/master/01.DQN.ipynb



2. 
   

   Multi-Step Learning (from Reinforcement Learning: An Introduction, Chapter 7) 

   
   

   [Publication] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/01.DQN.ipynb

   
   

   [code] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/02.NStep_DQN.ipynb



3. 
   

   Deep Reinforcement Learning with Double Q-learning 

   
   

   [Publication] 

   https://arxiv.org/abs/1509.06461

   
   

   [code] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/03.Double_DQN.ipynb



4. 
   

   Dueling Network Architectures for Deep Reinforcement Learning 

   [Publication] 

   https://arxiv.org/abs/1511.06581

   
   

   [code] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/04.Dueling_DQN.ipynb



5. 
   

   Noisy Networks for Exploration 

   [Publication] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/04.Dueling_DQN.ipynb

   
   

   [code] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/05.DQN-NoisyNets.ipynb



6. 
   

   Prioritized Experience Replay 

   [Publication] 

   https://arxiv.org/abs/1511.05952?context=cs

   
   

   [code] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/06.DQN_PriorityReplay.ipynb



7. 
   

   A Distributional Perspective on Reinforcement Learning 

   [Publication] 

   https://arxiv.org/abs/1707.06887

   
   

   [code] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/07.Categorical-DQN.ipynb



8. 
   

   Rainbow: Combining Improvements in Deep Reinforcement Learning 

   [Publication]

    https://arxiv.org/abs/1710.02298

   
   

   [code] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/08.Rainbow.ipynb



9. 
   

   Distributional Reinforcement Learning with Quantile Regression 

   
   

   [Publication] 

   https://arxiv.org/abs/1710.10044

   
   

   [code] 

   https://github.com/qfettes/DeepRL-Tutorials/blob/master/09.QuantileRegression-DQN.ipynb



10. 
    

    Rainbow with Quantile Regression 

    
    

    [code] 

    https://github.com/qfettes/DeepRL-Tutorials/blob/master/10.Quantile-Rainbow.ipynb



11. 
    

    Deep Recurrent Q-Learning for Partially Observable MDPs 

    
    

    [Publication] 

    https://arxiv.org/abs/1507.06527

    
    

    [code] 

    https://github.com/qfettes/DeepRL-Tutorials/blob/master/11.DRQN.ipynb



12. 
    

    Advantage Actor Critic (A2C) 

    
    

    [Publication1] 

    https://arxiv.org/abs/1602.01783

    
    

    [Publication2] 

    https://blog.openai.com/baselines-acktr-a2c/

    
    

    [code] 

    https://github.com/qfettes/DeepRL-Tutorials/blob/master/12.A2C.ipynb



13. 
    

    High-Dimensional Continuous Control Using Generalized Advantage Estimation 

    
    

    [Publication] 

    https://arxiv.org/abs/1506.02438

    
    

    [code] 

    https://github.com/qfettes/DeepRL-Tutorials/blob/master/13.GAE.ipynb



14. 
    

    Proximal Policy Optimization Algorithms 

    
    

    [Publication] 

    https://arxiv.org/abs/1707.06347

    
    

    [code] 

    https://github.com/qfettes/DeepRL-Tutorials/blob/master/14.PPO.ipynb

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【資源】機器學習演算法工程師手冊（PDF下載）

源碼 | Python爬蟲之網易雲音樂下載

548頁MIT強化學習教程，收藏備用【PDF下載】

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