Abstract
In this paper, we conducted a study to develop self-study materials with the ability to provide more suitable materials for students' skills. A first person shooter (FPS) type simulator-based teaching material is created to acquire knowledge. Conventional games resume from a predetermined scene regardless of trainee's skill contributes to no increases in knowledge and skill. In this paper, we propose a re-spawning point suitable for each trainee by a recommendation algorithm which tries to find good game scenes by trial and error.
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Kubo, M., Ueno, T., & Sato, H. (2020). Customization of contents for acquisition of skills of fps without trainer. In Proceedings of International Conference on Artificial Life and Robotics (Vol. 2020, pp. 767–769). ALife Robotics Corporation Ltd. https://doi.org/10.5954/ICAROB.2020.OS17-1
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