MAS4Games: A Reinforced Learning-Based Multi-agent System to Improve Player Retention in Virtual Reality Video Games
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49368-3_7
Reference13 articles.
1. Asperti, A., Cortesi, D., Pieri, C.D., Pedrini, G., Sovrano, F.: Crawling in rogue’s dungeons with deep reinforcement techniques. IEEE Trans. Games 12(2), 177–186 (2020)
2. Bojanić, M., Bojanić, G.: Self-learning mechanism for mobile game adjustment towards a player. Appl. Sci. 11, 4412 (2021)
3. Fernandes, W.R., Levieux, G.: Difficulty pacing impact on player motivation. In: Göbl, B., van der Spek, E., Baalsrud Hauge, J., McCall, R. (eds.) ICEC. LNCS, vol. 13477, pp. 140–153. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-20212-4_11
4. Fernández-Samillán, D., Guizado-Díaz, C., Ugarte, W.: Story creation algorithm using Q- learning in a 2D action RPG video game. In: IEEE FRUCT, pp. 111–117 (2021)
5. Lazaridis, A., Vlahavas, I.P.: REIN-2: giving birth to prepared reinforcement learning agents using reinforcement learning agents. Neurocomputing 497, 86–93 (2022)
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