Title: | Using 2048-like games as a pedagogical tool for reinforcement learning |
Authors: | Guei, Hung Wei, Ting-Han Wu, I-Chen 資訊工程學系 Department of Computer Science |
Keywords: | 2048 game;computer science;reinforcement learning;pedagogy;education |
Issue Date: | 1-Jan-2018 |
Abstract: | 2048-like games are games that have similar properties with 2048, a single-player stochastic sliding puzzle game. 2048-like games are highly suitable for educational purposes due to 2048's relatively simple rules and its popularity. When using 2048-like games as a tool for machine learning education, these games have the additional benefit of being a well-known topic of research. Numerous machine learning methods have been proposed in the past for 2048, which provides a good opportunity for students to gain first-hand experience in applying these techniques. This paper summarizes the experience of using the game 2584, a 2048-like game, as a pedagogical tool for teaching reinforcement learning and computer game algorithms in 2017. 2584 is similar to 2048, with the only difference being the tiles values are Fibonacci numbers instead of powers of two. A two-player variant was designed to further teach adversarial game techniques. With a class of 33 undergraduate and graduate students, the average win rate for the single-player version of the 2584 reached 96%. |
URI: | http://dx.doi.org/10.3233/ICG-180062 http://hdl.handle.net/11536/148959 |
ISSN: | 1389-6911 |
DOI: | 10.3233/ICG-180062 |
Journal: | ICGA JOURNAL |
Volume: | 40 |
Begin Page: | 281 |
End Page: | 293 |
Appears in Collections: | Articles |