Is there any tutorial that walks through a multi-agent reinforcement learning implementation (in Python) using libraries such as OpenAI's Gym (for the environment), TF-agents, and stable-baselines-3?
I searched a lot, but I was not able to find any tutorial, mostly because Gym environments and most RL libraries are not for multi-agent RL.
After checking the Internet, you will probably find several resources such as
Try to understand the principles first (see above). After some reasonable amount of coding you can adapt OpenAI gym. Good luck!
Update 17 March 2022:
You may want to check this popular repository as well https://github.com/Farama-Foundation/PettingZoo
Update 06 August 2023:
The best multi-agent tutorial I have seen so far comes from RLlib documentation. See RLlib for muti-agent RL.
Multi-Agent Deep Reinforcement Learning in 13 Lines of Code Using PettingZoo
A tutorial on multi-agent deep reinforcement learning for beginners.
This tutorial provides a simple introduction to using multi-agent reinforcement learning, assuming a little experience in machine learning and knowledge of Python.
Hugging Face RL Tutorial has a practical tutorial on Multi-agent reinforcement learning.
For those who want to dive deeper, it has a reading list at the end that covers its theory and more advance techniques.
