Fighting Game Adaptive Background Music for Improved Gameplay
Abstract: This paper presents our work to enhance the background music (BGM) in DareFightingICE by adding adaptive features. The adaptive BGM consists of three different categories of instruments playing the BGM of the winner sound design from the 2022 DareFightingICE Competition. The BGM adapts by changing the volume of each category of instruments. Each category is connected to a different element of the game. We then run experiments to evaluate the adaptive BGM by using a deep reinforcement learning AI agent that only uses audio as input (Blind DL AI). The results show that the performance of the Blind DL AI improves while playing with the adaptive BGM as compared to playing without the adaptive BGM.
- I. Khan, T. V. Nguyen, X. Dai, and R. Thawonmas, “DareFightingICE Competition: A Fighting Game Sound Design and AI Competition,” 2022 IEEE Conference on Games (CoG), pp. 478–485, 2022.
- F. Lu, K. Yamamoto, L. H. Nomura, S. Mizuno, Y. M. Lee, and R. Thawonmas, “Fighting Game Artificial Intelligence Competition Platform,” 2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE), pp. 320–323, Oct. 2013. (https://www.ice.ci.ritsumei.ac.jp/ ftgaic/index.htm)
- T. Van Nguyen, X. Dai, I. Khan, R. Thawonmas, and H. V. Pham, “A Deep Reinforcement Learning Blind AI in DareFightingICE,” 2022 IEEE Conference on Games (CoG), pp. 632–637, 2022.
- Moises Systems. 2023. Moises. [Online]. Available: https://moises.ai/
- M. Ishihara, T. Miyazaki, C. Y. Chu, T. Harada, and R. Thawonmas, “Applying and Improving Monte-Carlo Tree Search in a Fighting Game AI,” in Proceedings of the 13th International Conference on Advances in Computer Entertainment Technology, pp. 1-6, Nov. 2016.
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