Introduction
Reinforcement learning agent for Google Research Football.
Code accompanying the paper "TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play" (AAMAS 2023).
Installation
- 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
.
Convert dump file to video
After the installation, you can use tizero to convert a dump file to a video file.
The usage is tizero dump2video <dump_file> <output_dir> --episode_length <the length> --render_type <2d/3d>
.
You can download an example dump file from here.
And then execute tizero dump2video daily_6484285.dump ./
in your terminal. By default, the episode length is 3000 and the render type is 2d.
Wait a minute, you will get a video file named daily_6484285.avi
in your current directory.
Submit TiZero to JIDI(及第评测平台)
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.
You can submit this agent to JIDI directly.
Cite
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}
}