(A)I Will Teach You to Play Gomoku: Exploring the Use of Game AI to Teach People
Proceedings of the Ninth ACM Conference on Learning @ Scale
2022
Abstract
Artificial intelligence systems such as AlphaGo, AlphaGo Zero and AlphaZero, have demonstrated their advantages and competency over human players. However, little research has explored the possibility of applying such algorithms for educational purposes, such as teaching people to play strategy games. To investigate this gap, we designed and developed a Gomoku tutor that can provide instant/delayed feedback to users. We trained an expert model for Gomoku from scratch by using an open-source AlphaZero implementation and embedded this model into our Gomoku tutoring system. We plan to use this tutor to investigate two main research questions: 1) Can Game AI models, which are inhuman in their expertise, provide guidance that improves human learning? 2) How do different types of Game AI derived feedback affect people's learning outcomes? In this paper, we outline our experimental plans to investigate these questions.
BibTeX
@inproceedings{zhang-las-2022,
title = {(A)I Will Teach You to Play Gomoku: Exploring the Use of Game AI to Teach People},
author = {Zhang, Qiao and MacLellan, Christopher J.},
booktitle = {Proceedings of the Ninth ACM Conference on Learning @ Scale},
pages = {263-266},
year = {2022},
doi = {10.1145/3491140.3528331},
}