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[P] Implementations of basic RL algorithms with minimal codes!

[PyTorch Based]

Hi,

for those of you who are interested in RL,

I recently implemented basic RL algorithms such as

REINFORCE, vanilla actor-critic, DDPG, A3C, DQN and PPO with PyTorch.

Characteristics are as follows :

  • Each algorithm is complete within a single file.
  • Length of each algorithm is up to 100~150 lines of codes.
  • Every algorithm can be trained within 30 seconds, even without GPU.
  • Envs are fixed to “CartPole-v1”. You can just focus on the implementations.

As you can see in the name of the repository,

I tried to make the code as brief and intuitive as possible.

Hope you enjoy 🙂

Thank you.

https://github.com/seungeunrho/minimalRL

submitted by /u/seungeun07
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.