Masao Kubo, Takeshi Ueno, Hiroshi Sato
Department of Computer Science, National Defense Academy, Hashirimizu-10-20, Yokosuka, Kanagawa 239-8686, Japan
pp. 138-143
ABSTRACT
In this paper, we propose an approach to customize the E-learning of video game-like by trial and error. A virtual training environment is getting to be common in military training, however, it is still underway to use it as a self-learning tool because of a lack of suitable training curricula for each trainee. First Person Shooting game (FPS) environment which is adequate for such the training, but a lot of characters and objects there which can be considered as the customizing point may cause combinatorial problems in traditional approaches. We show our method based on respawning point can present tasks to trainees by reinforcement learning and they can reach the goal faster than other content generation methods.

ARTICLE INFO
Article History
Received 26 November 2019
Accepted 23 August 2020

Keywords
Content generation
Reinforcement learning
E-Learning
Game AI
Video game
Virtual reality

JAALR1307

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