【代码集合】深度强化学习Pytorch实现集锦

本次分享的是用PyTorch语言编写的深度强化学习算法的高质量实现，这些IPython笔记本的目的主要是帮助练习和理解这些论文；因此，在某些情况下，我将选择可读性而不是效率。首先，我会上传论文的实现，然后是标记来解释代码的每一部分。

相关论文

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

PyTorch实现