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.idea
.idea
 
 
.ipynb_checkpoints
.ipynb_checkpoints
 
 
alphago
alphago
 
 
runs
runs
 
 
saved_models
saved_models
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 
actor_critic.py
actor_critic.py
 
 
actor_model.pt
actor_model.pt
 
 
actor_modelbreakout.pt
actor_modelbreakout.pt
 
 
actor_modelpong.pt
actor_modelpong.pt
 
 
cleanrl_sac.py
cleanrl_sac.py
 
 
critic_model pong.pt
critic_model pong.pt
 
 
critic_model.pt
critic_model.pt
 
 
ddpg_from_scratch.py
ddpg_from_scratch.py
 
 
ddpg_pendulum.zip
ddpg_pendulum.zip
 
 
ddqn.ipynb
ddqn.ipynb
 
 
dqn_cliffwalking.ipynb
dqn_cliffwalking.ipynb
 
 
dqn_cuda.ipynb
dqn_cuda.ipynb
 
 
dqn_cuda.py
dqn_cuda.py
 
 
dqn_non_image_cuda.py
dqn_non_image_cuda.py
 
 
dummy_envs.py
dummy_envs.py
 
 
dyna.py
dyna.py
 
 
linux_ppo_vec_envs_image copy.py
linux_ppo_vec_envs_image copy.py
 
 
linux_ppo_vec_envs_image.py
linux_ppo_vec_envs_image.py
 
 
mbrl.py
mbrl.py
 
 
policy_gradients.py
policy_gradients.py
 
 
policy_gradients_image.py
policy_gradients_image.py
 
 
ppo.py
ppo.py
 
 
ppo_cont_vec_envs_image.py
ppo_cont_vec_envs_image.py
 
 
ppo_copied_from_reddit.py
ppo_copied_from_reddit.py
 
 
ppo_single_env.py
ppo_single_env.py
 
 
ppo_vec_envs.py
ppo_vec_envs.py
 
 
ppo_vec_envs_image.py
ppo_vec_envs_image.py
 
 
ppo_vec_envs_image_inference.py
ppo_vec_envs_image_inference.py
 
 
procgen_prototype.py
procgen_prototype.py
 
 
q_learning_cliff_walking_environment.ipynb
q_learning_cliff_walking_environment.ipynb
 
 
sac.py
sac.py
 
 
sac_clean_rl.py
sac_clean_rl.py
 
 
sac_copying_cleanrl_approximator.py
sac_copying_cleanrl_approximator.py
 
 
sac_load.py
sac_load.py
 
 
saved_rl_breakout.gif
saved_rl_breakout.gif
 
 
saved_rl_videobreakout.gif
saved_rl_videobreakout.gif
 
 
saved_rl_videopong.gif
saved_rl_videopong.gif
 
 
sb3_ddpg.py
sb3_ddpg.py
 
 
sb3_ppo.py
sb3_ppo.py
 
 
sb3_ppo_envpool.py
sb3_ppo_envpool.py
 
 
tot_rewards.csv
tot_rewards.csv
 
 
tot_rewards_ddpg.csv
tot_rewards_ddpg.csv
 
 

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Here is my implementation of popular RL algorithms. I referred many popular code bases while writing my implementations.

The algorithms I have implemented are -

  1. DQN
  2. PPO
  3. DDQN
  4. PG (Work needed)
  5. DDPG (Work needed)
  6. SAC (Work needed)

Trained Agents -

Pong       Breakout

About

Practicing various RL algorithms

Topics

reinforcement-learning

Resources

Readme

License

MIT license
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