Dynamic Difficulty Adjustment for a Memory Game
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-05532-5_46
Reference15 articles.
1. Andrade, G., Ramalho, G., Santana, H., Corruble, V.: Automatic computer game balancing: a reinforcement learning approach. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2005, pp. 1111–1112. ACM, New York (2005). https://doi.org/10.1145/1082473.1082648
2. Bouker, J., Scarlatos, A.: Investigating the impact on fluid intelligence by playing N-Back games with a kinesthetic modality. In: 2013 10th International Conference and Expo on Emerging Technologies for a Smarter World (CEWIT), pp. 1–3, October 2013. https://doi.org/10.1109/CEWIT.2013.6713747
3. Brehmer, Y., Westerberg, H., Bckman, L.: Working-memory training in younger and older adults: training gains, transfer, and maintenance. Front. Hum. Neurosci. 6, 63 (2012). https://doi.org/10.3389/fnhum.2012.00063
4. Chacko, A., et al.: A randomized clinical trial of Cogmed Working Memory Training in school-age children with ADHD: a replication in a diverse sample using a control condition. J. Child Psychol. Psychiatry Allied Discipl. 55(3), 247–255 (2014). https://doi.org/10.1111/jcpp.12146
5. Deveau, J., Jaeggi, S.M., Zordan, V., Phung, C., Seitz, A.R.: How to build better memory training games. Front. Syst. Neurosci. 8, 243 (2015). https://doi.org/10.3389/fnsys.2014.00243
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