Romero-Mendez, E.A.; Santana-Mancilla, P.C.; Garcia-Ruiz, M.; Montesinos-López, O.A.; Anido-Rifón, L.E.
The Use of Deep Learning to Improve Player Engagement in a Video Game through a Dynamic Difficulty Adjustment Based on Skills Classification. Appl. Sci. 2023, 13, 8249.
https://doi.org/10.3390/app13148249
AMA Style
Romero-Mendez EA, Santana-Mancilla PC, Garcia-Ruiz M, Montesinos-López OA, Anido-Rifón LE.
The Use of Deep Learning to Improve Player Engagement in a Video Game through a Dynamic Difficulty Adjustment Based on Skills Classification. Applied Sciences. 2023; 13(14):8249.
https://doi.org/10.3390/app13148249
Chicago/Turabian Style
Romero-Mendez, Edwin A., Pedro C. Santana-Mancilla, Miguel Garcia-Ruiz, Osval A. Montesinos-López, and Luis E. Anido-Rifón.
2023. "The Use of Deep Learning to Improve Player Engagement in a Video Game through a Dynamic Difficulty Adjustment Based on Skills Classification" Applied Sciences 13, no. 14: 8249.
https://doi.org/10.3390/app13148249
APA Style
Romero-Mendez, E. A., Santana-Mancilla, P. C., Garcia-Ruiz, M., Montesinos-López, O. A., & Anido-Rifón, L. E.
(2023). The Use of Deep Learning to Improve Player Engagement in a Video Game through a Dynamic Difficulty Adjustment Based on Skills Classification. Applied Sciences, 13(14), 8249.
https://doi.org/10.3390/app13148249