Minimal Agents

This repository contains a minimal implementation of a tabular Q-learning, SARSA and R-max agents (other types of agents to be included in the future). The agents are pretty simple and can be used as baselines or a starting point for more advanced algorithms.

Table of Contents

1. Installation
   • Installing via uv
   • Installing via pip
2. Usage
3. Contributing
4. License

Installation

You can install this package using either pip or uv (a minimal package manager/distribution manager example in Python). Note: If you're unfamiliar with uv, you can skip directly to the pip instructions.

1. Installing via uv

uv add https://github.com/cruz-lucas/minimal_agents.git

This should handle the necessary dependencies and set up the virtual environment if you have a pyproject.toml file, if not, see use uv init.

2. Installing via pip

pip install git+https://github.com/cruz-lucas/minimal_agents.git

This command installs the RiverSwim environment into your Python environment (consider using a virtual environment).

Usage

Once installed, you can use the agents in your Python code. You can find examples of usage in the examples.

Contributing

Contributions and suggestions to improve this minimal implementation are always welcome. Feel free to open an issue or a pull request.

License

This project is licensed under the MIT License. Please see the LICENSE file for more information.