![](http://deeprlhub.com/assets/files/2021-02-09/1612840105-301665-image.png)
![](http://deeprlhub.com/assets/files/2021-02-09/1612840131-930828-image.png)
![](http://deeprlhub.com/assets/files/2021-02-09/1612840186-20852-image.png)
![](http://deeprlhub.com/assets/files/2021-02-09/1612840203-987613-image.png)
![](http://deeprlhub.com/assets/files/2021-02-09/1612840220-158901-image.png)
This project is used for the Generic Video Game Competition (GVGAI) Learning Competition since the year 2019. For more about the competition legs, rules and rank, please visite the AI in Games website, maintained by Hao Tong and Jialin Liu.
Disclamer
This project is forked from GVGAI Gym, which is an OpenAI Gym environment for games written in the Video Game Description Language (VGDL), including the GVGAI framework.
Please refer to the paper Deep Reinforcement Learning for General Video Game AI for more about the GVGAI GYM framework and some initial results of Reinforcement Learning (RL) agents. This paper should be cited if code from this project or the original GVGAI GYM project is used in any way:
@inproceedings{torrado2018deep,
title={Deep Reinforcement Learning for General Video Game AI},
author={Torrado, Ruben Rodriguez and Bontrager, Philip and Togelius, Julian and Liu, Jialin and Perez-Liebana, Diego},
booktitle={Computational Intelligence and Games (CIG), 2018 IEEE Conference on},
year={2018},
organization={IEEE}
}
![](http://deeprlhub.com/assets/files/2021-02-09/1612840300-34407-image.png)
![](http://deeprlhub.com/assets/files/2021-02-09/1612840317-576951-image.png)