Deep-Reinforcement-Learning-with-pytorch
Deep-Reinforcement-Learning-with-pytorch copied to clipboard
LxzGordon
Basic reinforcement learning algorithms. Including:DQN,Double DQN, Dueling DQN, SARSA, REINFORCE, baseline-REINFORCE, Actor-Critic,DDPG,DDPG for discrete action space, A2C, A3C, TD3, SAC, TRPO
Deep-RL-with-pytorch
Practice for deep reinforcement learning algorithms by a starter.
Test environment is Gym-CartPolev0 for discrete action space and Gym-PendulmV0 for continuous action space.
Under active development.
Including:DQN, REINFORCE, baseline-REINFORCE, Actor-Critic, Double DQN, Dueling DQN, Sarsa, DDPG, DDPG for discrete action space, A2C, A3C, TD3, SAC, TRPO
2020-9-19 implement
algorithm:
1.DQN
2.REINFORCE
components:
1.experience replay
2020-9-20 implement
algorithm:
1.baseline-REINFORCE
2.Actor-Critic
Add CUDA support
2021-1-15 implement
algorithm:
1.Double DQN
2.Dueling DQN
2021-1-19 implement
algorithm:
1.Sarsa
2021-1-23 implement
algorithm:
1.DDPG
2.DDPG for discrete action space using gumbel softmax
2021-1-26 implement
algorithm:
1.A2C
2021-1-27 implement
algorithm:
1.A3C
2021-2-4 implement
algorithm:
1.TD3
2.SAC
2021-2-25 implement
algorithm:
1.TRPO(Natural Policy gradient).
Unknown bug exists: Hessian matrix may not be positive definite at the beginning of training(But the training will usually converge)
LxzGordon