INNK: A DEEP LEARNING GAME
This project is a collaboration between Drs. Jichen Zhu (Digital Media, Drexel) and Sebastian Risi (Digital Design, IT University of Copenhagen).
iNNK, a multiplayer drawing game where human players team up against a neural network (NN). The players need to successfully communicate a secret code word to each other through drawings, without being deciphered by the NN. With this game, we aim to foster a playful environment where players can, in a small but crucial way, go from passive consumers of NN applications to creative thinkers and critical challengers.
Twitter: @iNNkGame
Team members
Active members: Boyd Fox, Yifu Li, Mathias Löwe, Sebastian Risi, Alex Sladek, Jen Villareale, LingAn Zheng, Jichen Zhu
Past members: Ana Acosta, Andrew Bishop, Panote Nuchprayoon, Rush Weigelt, Samuel Arcaro, Evan Freed, Robert Gray
Publications
CONFERENCE PROCEEDINGS
- M. Löwe, J. Villareale, E. Freed, A. Sladek, J. Zhu, and S. Risi, “Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning” in Proceedings of the Foundation of Digital Games Conference (FDG’21), 2021. Best Paper Award
- J. Villareale, A. Acosta-Ruiz, S. Arcaro, T. Fox, E. Freed, R. Gray, M. Löwe, P. Nuchprayoon, A. Sladek, R. Weigelt, Y. Li, S. Risi and J. Zhu, “iNNk: A Multi-Player Game to Deceive a Neural Network” in Proceedings of the 2020 ACM Conference of CHI PLAY (CHI Play 2020), 2020