Reinforcement learning agent for Google Research Football.
Code accompanying the paper "TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play" (AAMAS 2023). [paper] [videos].
- Follow the instructions in gfootball to set up the environment.
pip install gfootball
pip install tizero
(or clone this repo andpip install -e .
).- test the installation by
python3 -m gfootball.play_game --action_set=full
.
After the installation, you can use tizero to convert a dump file to a video file.
You can download an example dump file from here.
And then execute tizero --tool dump2video --input daily_6484285.dump --output ./
in your terminal.
Wait a minute, you will get a video file named daily_6484285.avi
in your current directory.
JIDI is a public evaluation platform for RL agents. You can submit your agent of GRF at: http://www.jidiai.cn/env_detail?envid=34.
We provide two agents under ./submission/
directory:
./submission/tizero
: the final model of TiZero for JIDI submission, which ranked 1st on October 28th, 2022../submission/random_agent
: the random agent for JIDI submission.
Please cite our paper if you use our codes or our weights in your own work:
@article{lin2023tizero,
title={TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play},
author={Lin, Fanqi and Huang, Shiyu and Pearce, Tim and Chen, Wenze and Tu, Wei-Wei},
journal={arXiv preprint arXiv:2302.07515},
year={2023}
}