Implementations of reinforcement learning algorithms by PyTorch
I found the current implementations of Reinforcement Learning Algorithms are somewhat complicated, which is hard to get start.
Here are some classical Reinforcement Learning Algorithms implemented by Pytorch. I tried to make them clean, robust, and unified, hoping to help you get start with RL quickly.
Now I have finished Q-learning, DQN, DDQN, PPO discrete, PPO continuous, TD3, SAC Continuous, SAC Discrete. I will implement more in the future.