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Neural Computing and Applications
Published in: Neural Computing and Applications 15/2021

19-06-2021 | S.I. : Neuro, fuzzy and their hybridization

BiLSTM and dynamic fuzzy AHP-GA method for procedural game level generation

Author: Murat İnce

Published in: Neural Computing and Applications | Issue 15/2021

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Abstract

The use of games in daily life, especially in education, has been in an incline during the COVID-2019 pandemic. Thus, game-based learning environments have caused an increase in the need of game contents, but generation of the game contents and levels is a time-consuming and costly process. Generated game contents and levels should be balanced, dense, aesthetic and reachable. Also, the time as well as the costs spent should be decreased. In order to overcome this problem, automatic and intelligent game content and level generation methods have emerged, and procedural content generation (PCG) is the most popular one of these methods. Artificial intelligence techniques are used for procedural game level generation instead of traditional methods. In this study, bidirectional long short-term memory (BiLSTM) and fuzzy analytic hierarchy process-genetic algorithm (FAHP-GA) methods were used to generate procedural game levels. This proposed hybrid system was used in a developed educational game as a case study to create game levels. The performance of the proposed study was compared to the other multi-criteria decision-making (MCDM) methods, and also further statistical analyses were investigated. The results showed that the BiLSTM-based FAHP-GA method can be used for procedural game level generation effectively.
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Metadata
Title
BiLSTM and dynamic fuzzy AHP-GA method for procedural game level generation
Author
Murat İnce
Publication date
19-06-2021
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 15/2021
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-021-06180-7

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