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About ReinforceX
ReinforceX (ReX) is a deep reinforcement learning framework built entirely from scratch in Rust. We plan to implement various reinforcement learning algorithms, including value-based, policy-based, and actor-critic methods.
Advantages of Rust: Efficient memory management prevents memory leaks that often trouble data scientists when using Python. Enables thread-safe execution for parallel training. Offers overall faster training speeds compared to Python-based frameworks.
Algorithms
| Name | Status |
|---|---|
| REINFORCE | Done |
| DQN | Done |
| PPO | Not yet |
| SAC | Not yet |
Sample experiments
The experimental environment is built using OpenAI Gym. Since Gym is a Python framework, set up a Python environment and run the following pip command:
pip install gymnasium==0.26.3
We use Gym as the environment by calling Python from Rust.
cargo run -- --env cartpole --algo dqn
Unit test
cargo test
License
MIT License (https://github.com/kakky-hacker/reinforcex/blob/master/LICENSE)