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reinforcement-learning's Introduction

reinforcement learning

reinforcement learning algorithms implementation with pytorch

reference:

https://github.com/AI4Finance-LLC/ElegantRL (DRL algo impl)

https://github.com/starry-sky6688/StarCraft (MARL algo impl)

content

1.Tabular:

  • MazeEnv: my gmy-like environment, for tabular algos

  • MonteCarlo

  • off-policy MonteCarlo (with important sampling)

  • Sarsa

  • QLearning

  • DoubleQLearning

  • n-step Sarsa

  • Sarsa(lambda)

2.Deep Q Network

  • Deep Q Network

  • DDQN(Double DQN)

  • Dueling DQN

  • D3QN(Dueling DDQN)

3.Policy Gradient

  • REINFORCE

  • REINFORCE with baseline

4.Deterministic Policy Gradient

  • DDPG(Deep Deterministic Policy Gradient)

  • TD3(Twin Delayed DDPG)

5.Actor Critic

  • PPO(Proximal Policy Optimization) (PPO-Clip)

6.Multi-Agent RL

(Env: Multi-Agent partical world)

  • Qmix

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