Version 1
: Received: 5 September 2024 / Approved: 6 September 2024 / Online: 6 September 2024 (12:10:14 CEST)
How to cite:
Vaghani, V.; Oyibo, K. A Scoping Review of Genetic Algorithms in Serious Games: Applications, Challenges, and
Future Directions. Preprints2024, 2024090531. https://doi.org/10.20944/preprints202409.0531.v1
Vaghani, V.; Oyibo, K. A Scoping Review of Genetic Algorithms in Serious Games: Applications, Challenges, and
Future Directions. Preprints 2024, 2024090531. https://doi.org/10.20944/preprints202409.0531.v1
Vaghani, V.; Oyibo, K. A Scoping Review of Genetic Algorithms in Serious Games: Applications, Challenges, and
Future Directions. Preprints2024, 2024090531. https://doi.org/10.20944/preprints202409.0531.v1
APA Style
Vaghani, V., & Oyibo, K. (2024). A Scoping Review of Genetic Algorithms in Serious Games: Applications, Challenges, and
Future Directions. Preprints. https://doi.org/10.20944/preprints202409.0531.v1
Chicago/Turabian Style
Vaghani, V. and Kiemute Oyibo. 2024 "A Scoping Review of Genetic Algorithms in Serious Games: Applications, Challenges, and
Future Directions" Preprints. https://doi.org/10.20944/preprints202409.0531.v1
Abstract
The integration of Genetic Algorithms (GAs) into Serious Games (SGs) has gained traction
as a method to optimize game mechanics and personalize user experiences. While GAs are
well-known for their effectiveness in solving complex optimization problems, their application in
SGs remains relatively under-explored. This review aims to address this gap by systematically
mapping the existing literature on the intersection of these two fields. The primary objective
of this scoping review is to identify and synthesize the existing research on the application of
GAs in SGs, with a focus on understanding the current state of the field, identifying common
applications, challenges, and potential future directions. The review includes studies published in
English that focus on the use of GAs within SGs. The search encompassed articles from academic
journals and conference proceedings without restrictions on publication dates. Exclusion criteria
included studies that did not specifically address the integration of GAs in SGs. A systematic
search was conducted in databases such as ACM Digital Library, Web of Science, Scopus
and Inspec in July 2024. The search terms used included "genetic algorithm," "evolutionary
algorithm," "computational algorithm," and "serious games." Unpublished data and articles
were not considered. Data were charted using a PRISMA flowchart developed by the author
VV. Key categories for data extraction included study objectives, methods, outcomes, type of
study and GA used and the specific applications of GAs in SGs. Data charting was conducted
independently by two reviewers, with disagreements resolved through discussion and consensus.
The search identified 154 studies, of which 23 met the inclusion criteria. The included studies
highlight the diverse applications of GAs in SGs, ranging from optimizing game scenarios to
personalizing learning experiences. Challenges identified include the computational complexity
of GAs and difficulties in their integration into existing game frameworks. The findings of this
review suggest that while the use of GAs in SGs is a promising area of research, it remains in its
nascent stages. Future research should focus on addressing the technical challenges of integrating
GAs into SGs and exploring their application across a wider range of game genres and educational
contexts. Limitations of the review include the potential for publication bias and the exclusion of
non-English language studies.
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
