MyRL

Welcome to MyRL, a Rust-based project for exploring reinforcement learning concepts and implementations.

Features

• Written in Rust for performance and safety.
• Modular design for easy experimentation.
• Support for various RL algorithms.

Getting Started

1. Clone the repository:

   git clone https://github.com/yourusername/myrl.git
   cd myrl

2. Build the project:

   cargo build

3. Run examples:

   cargo run --example example_name

Dependencies

The project relies on the following dependencies:

• rand: For random number generation.
• serde: For serialization and deserialization.
• ndarray: For numerical computations.
• thiserror: For error handling.

Make sure to check the Cargo.toml file for the exact versions.

TODOs

• Implement additional RL algorithms such as DDPG and PPO.
• Add unit tests for core modules.
• Improve documentation with detailed examples and use cases.
• Optimize performance for large-scale simulations.
• Create a benchmarking suite to compare algorithm performance.
• Add support for custom environments.
• Refactor code for better readability and maintainability.
• Write a tutorial for beginners to get started with the project.
• Explore integration with visualization tools for better insights.
• Publish the project on crates.io for wider accessibility.