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@@ -30,25 +30,26 @@ similar to file with ```eval```, which means to evaluate the agent.
## Schedule
| Name | Related materials | Used Envs | Notes |
| :--------------------------------------: | :----------------------------------------------------------: | ------------------------------------- | :---: |
| [On-Policy First-Visit MC](./MonteCarlo) | | [Racetrack](./envs/racetrack_env.md) | |
| [Q-Learning](./QLearning) | | [CliffWalking-v0](./envs/gym_info.md) | |
| [Sarsa](./Sarsa) | | [Racetrack](./envs/racetrack_env.md) | |
| [DQN](./DQN) | [DQN-paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf),[Nature DQN Paper](https://www.nature.com/articles/nature14236) | [CartPole-v0](./envs/gym_info.md) | |
| [DQN-cnn](./DQN_cnn) | [DQN-paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf) | [CartPole-v0](./envs/gym_info.md) | |
| [DoubleDQN](./DoubleDQN) | | [CartPole-v0](./envs/gym_info.md) | |
| [Hierarchical DQN](HierarchicalDQN) | [Hierarchical DQN](https://arxiv.org/abs/1604.06057) | [CartPole-v0](./envs/gym_info.md) | |
| [PolicyGradient](./PolicyGradient) | | [CartPole-v0](./envs/gym_info.md) | |
| [A2C](./A2C) | [A3C Paper](https://arxiv.org/abs/1602.01783) | [CartPole-v0](./envs/gym_info.md) | |
| [SAC](./SAC) | [SAC Paper](https://arxiv.org/abs/1801.01290) | | |
| [PPO](./PPO) | [PPO paper](https://arxiv.org/abs/1707.06347) | [CartPole-v0](./envs/gym_info.md) | |
| [DDPG](./DDPG) | [DDPG Paper](https://arxiv.org/abs/1509.02971) | [Pendulum-v0](./envs/gym_info.md) | |
| [TD3](./TD3) | [TD3 Paper](https://arxiv.org/abs/1802.09477) | HalfCheetah-v2 | |
| Name | Related materials | Used Envs | Notes |
| :--------------------------------------: | :----------------------------------------------------------: | ----------------------------------------- | :---: |
| [On-Policy First-Visit MC](./MonteCarlo) | [medium blog](https://medium.com/analytics-vidhya/monte-carlo-methods-in-reinforcement-learning-part-1-on-policy-methods-1f004d59686a) | [Racetrack](./envs/racetrack_env.md) | |
| [Q-Learning](./QLearning) | [towardsdatascience blog](https://towardsdatascience.com/simple-reinforcement-learning-q-learning-fcddc4b6fe56),[q learning paper](https://ieeexplore.ieee.org/document/8836506) | [CliffWalking-v0](./envs/gym_info.md) | |
| [Sarsa](./Sarsa) | [geeksforgeeks blog](https://www.geeksforgeeks.org/sarsa-reinforcement-learning/) | [Racetrack](./envs/racetrack_env.md) | |
| [DQN](./DQN) | [DQN Paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf),[Nature DQN Paper](https://www.nature.com/articles/nature14236) | [CartPole-v0](./envs/gym_info.md) | |
| [DQN-cnn](./DQN_cnn) | [DQN Paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf) | [CartPole-v0](./envs/gym_info.md) | 与DQN相比使用了CNN而不是全链接网络 |
| [DoubleDQN](./DoubleDQN) | [DoubleDQN Paper](https://arxiv.org/abs/1509.06461) | [CartPole-v0](./envs/gym_info.md) | |
| [Hierarchical DQN](HierarchicalDQN) | [H-DQN Paper](https://arxiv.org/abs/1604.06057) | [CartPole-v0](./envs/gym_info.md) | |
| [PolicyGradient](./PolicyGradient) | [Lil'log](https://lilianweng.github.io/lil-log/2018/04/08/policy-gradient-algorithms.html) | [CartPole-v0](./envs/gym_info.md) | |
| [A2C](./A2C) | [A3C Paper](https://arxiv.org/abs/1602.01783) | [CartPole-v0](./envs/gym_info.md) | |
| [SAC](./SAC) | [SAC Paper](https://arxiv.org/abs/1801.01290) | [Pendulum-v0](./envs/gym_info.md) | |
| [PPO](./PPO) | [PPO paper](https://arxiv.org/abs/1707.06347) | [CartPole-v0](./envs/gym_info.md) | |
| [DDPG](./DDPG) | [DDPG Paper](https://arxiv.org/abs/1509.02971) | [Pendulum-v0](./envs/gym_info.md) | |
| [TD3](./TD3) | [TD3 Paper](https://arxiv.org/abs/1802.09477) | [HalfCheetah-v2]((./envs/mujoco_info.md)) | |
## Refs
[RL-Adventure-2](https://github.com/higgsfield/RL-Adventure-2)
[RL-Adventure](https://github.com/higgsfield/RL-Adventure)
[RL-Adventure](https://github.com/higgsfield/RL-Adventure)