seungeunrho/minimalRL
Educational repository implementing fundamental reinforcement learning algorithms in minimal PyTorch code.
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A collection of concise implementations of classic reinforcement learning algorithms including REINFORCE, Actor-Critic, DQN, PPO, DDPG, A3C, ACER, and SAC. Each algorithm is contained in a single file under 150 lines and can be trained on CartPole-v1 without GPU. The repository serves as a learning resource for understanding RL algorithm mechanics by providing readable, self-contained code.
Frequently asked
- What is seungeunrho/minimalRL?
- Educational repository implementing fundamental reinforcement learning algorithms in minimal PyTorch code.
- Is minimalRL open source?
- Yes — seungeunrho/minimalRL is open source, released under the MIT license.
- What language is minimalRL written in?
- seungeunrho/minimalRL is primarily written in Python.
- How popular is minimalRL?
- seungeunrho/minimalRL has 3.2k stars on GitHub.
- Where can I find minimalRL?
- seungeunrho/minimalRL is on GitHub at https://github.com/seungeunrho/minimalRL.