Project Structure

Here is an overview of the main components in RL-A2A:

RL-A2A/
├── algorithms/        # RL algorithms (A2A, A2C, PPO, etc.)
├── agents/            # Agent definitions and classes
├── environments/      # Environment wrappers and helpers
├── configs/           # Configuration files (YAML/JSON)
├── utils/             # Utility functions (logging, plotting, etc.)
├── experiments/       # Experiment scripts and results
├── tests/             # Unit and integration tests
├── train.py           # Main training script
├── eval.py            # Evaluation script
├── requirements.txt   # Python dependencies
└── README.md

• algorithms/: Core algorithm implementations.
• agents/: Agent logic and policy/value networks.
• environments/: Wrappers for Gym and custom environments.
• configs/: Experiment and hyperparameter settings.
• utils/: Logging, metrics, and helper functions.
• experiments/: Example scripts and reproducible results.
• tests/: Automated tests to ensure code quality.

For more details, see Implementation Details.