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| [第十三章 AlphaStar 论文解读](https://datawhalechina.github.io/easy-rl/#/chapter13/chapter13) | | |
## 算法实战
| 算法名称 | 相关论文材料 | 备注 | 环境 |
| :----------------------------------------------------------: | :---------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: |
| [On-Policy First-Visit MC](https://github.com/datawhalechina/easy-rl/tree/master/codes/MonteCarlo) | | 蒙特卡洛算法 | [Racetrack](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/racetrack_env.md) |
| [Q-Learning](https://github.com/datawhalechina/easy-rl/tree/master/codes/QLearning) | | | [CliffWalking-v0](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/gym_info.md) |
| [Sarsa](https://github.com/datawhalechina/easy-rl/tree/master/codes/Sarsa) | | | [Racetrack](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/racetrack_env.md) |
| [DQN](https://github.com/datawhalechina/easy-rl/tree/master/codes/DQN) | [DQN-paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf) | [DQN算法实战](https://blog.csdn.net/JohnJim0/article/details/109557173) | [CartPole-v0](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/gym_info.md) |
| DQN-cnn | [DQN-paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf) | 与DQN相比使用了CNN而不是全链接网络 | [CartPole-v0](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/gym_info.md) |
| [DoubleDQN](https://github.com/datawhalechina/easy-rl/tree/master/codes/DoubleDQN) | | | [CartPole-v0](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/gym_info.md) |
| Hierarchical DQN | [Hierarchical DQN](https://arxiv.org/abs/1604.06057) | | |
| [PolicyGradient](https://github.com/datawhalechina/easy-rl/tree/master/codes/PolicyGradient) | | | [CartPole-v0](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/gym_info.md) |
| [A2C](https://github.com/datawhalechina/easy-rl/tree/master/codes/A2C) | | | [CartPole-v0](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/gym_info.md) |
| A3C | | | |
| SAC | | | |
| [PPO](https://github.com/datawhalechina/easy-rl/tree/master/codes/PPO) | [PPO paper](https://arxiv.org/abs/1707.06347) | [PPO算法实战](https://blog.csdn.net/JohnJim0/article/details/115126363) | [CartPole-v0](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/gym_info.md) |
| DDPG | [DDPG Paper](https://arxiv.org/abs/1509.02971) | | [Pendulum-v0](https://github.com/datawhalechina/easy-rl/blob/master/codes/envs/gym_info.md) |
| TD3 | [Twin Dueling DDPG Paper](https://arxiv.org/abs/1802.09477) | | |
| GAIL | | | |
| 算法名称 | 相关论文材料 | 环境 | 备注 |
| :--------------------------------------: | :---------------------------------------------------------: | ------------------------------------- | :--------------------------------: |
| [On-Policy First-Visit MC](./codes/MonteCarlo) | | [Racetrack](./codes/envs/racetrack_env.md) | |
| [Q-Learning](./codes/QLearning) | | [CliffWalking-v0](./codes/envs/gym_info.md) | |
| [Sarsa](./codes/Sarsa) | | [Racetrack](./codes/envs/racetrack_env.md) | |
| [DQN](./codes/DQN) | [DQN-paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf) | [CartPole-v0](./codes/envs/gym_info.md) | |
| DQN-cnn | [DQN-paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf) | [CartPole-v0](./codes/envs/gym_info.md) | 与DQN相比使用了CNN而不是全链接网络 |
| [DoubleDQN](./codes/DoubleDQN) | | [CartPole-v0](./codes/envs/gym_info.md) | 效果不好，待改进 |
| Hierarchical DQN | [Hierarchical DQN](https://arxiv.org/abs/1604.06057) | | |
| [PolicyGradient](./codes/PolicyGradient) | | [CartPole-v0](./codes/envs/gym_info.md) | |
| A2C | | [CartPole-v0](./codes/envs/gym_info.md) | |
| A3C | | | |
| SAC | | | |
| [PPO](./codes/PPO) | [PPO paper](https://arxiv.org/abs/1707.06347) | [CartPole-v0](./codes/envs/gym_info.md) | |
| DDPG | [DDPG Paper](https://arxiv.org/abs/1509.02971) | [Pendulum-v0](./codes/envs/gym_info.md) | |
| TD3 | [Twin Dueling DDPG Paper](https://arxiv.org/abs/1802.09477) | | |
| GAIL | | | |
## 贡献者