@inproceedings{baf578022b8c4033a8dd575a44b1d132,
title = "Dynamic difficulty adjustment for a memory game",
abstract = "Working memory is an important function for human cognition, it is related to some skills, such as remembering information or developing a mental calculation. Several games have been developed to train the working memory. Nevertheless, sometimes the game does not adjust adequate to users. Consequently, they end up bored by the game and leave it. This article presents a system of dynamic adjustment of the difficulty for a working memory training game, which allows generating customized levels so that the users obtain a better performance during the training of the memory. The proposed system was tested with young people, the results show that the training performance was better in comparison with a classic game and provide a better game experience to the users.",
keywords = "ANFIS, DDA, Fuzzy, Machine learning, Memory game, N-back, Working memory training",
author = "Vladimir Araujo and Alejandra Gonzalez and Diego Mendez",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 4th International Conference on Technology Trends, CITT 2018 ; Conference date: 29-08-2018 Through 31-08-2018",
year = "2019",
doi = "10.1007/978-3-030-05532-5_46",
language = "English",
isbn = "9783030055318",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "605--616",
editor = "Miguel Botto-Tobar and Mayra D{\textquoteright}Armas and {Z{\'u}{\~n}iga S{\'a}nchez}, Miguel and Miguel Z{\'u}{\~n}iga-Prieto and Guillermo Pizarro",
booktitle = "Technology Trends - 4th International Conference, CITT 2018, Revised Selected Papers",
address = "Germany",
}