The game development process is becoming a
more detailed structure every day. The applications of artificial intelligence
(AI), which is a comprehensive information technology, have been closely
related to game technologies. In this study, the levelling process of a
2-dimensional (2D) platform game was investigated. The game developed and called
“Renga” has a basic gameplay. Game
data has been processed through an artificial neural network (ANN), k-nearest neighbour, decision and random
tree algorithms and deep learning model that is trained with gameplay and user
information. The classification process with the output data provides results
for the next game level. In this way, the most effective playability impression
that the developers offer to the game users has been created according to game.
Furthermore, the variety of difficulty calculated with dynamic data by the user
is provided by Renga, in which new
sections/levels are created with user-specific assets. Thus, the most efficient
gaming experience has been transferred to the users.
Artificial Intelligence Difficulty Adjustment Content Generation k-Nearest Neighbor Random Forest Artificial Neural Networks
Scientific Research Coordination Unit of Pamukkale University
2018FEBE003
2018FEBE003
Birincil Dil | İngilizce |
---|---|
Konular | Yapay Zeka |
Bölüm | Araştırma Makalesi |
Yazarlar | |
Proje Numarası | 2018FEBE003 |
Yayımlanma Tarihi | 30 Nisan 2020 |
Yayımlandığı Sayı | Yıl 2020 Cilt: 8 Sayı: 2 |
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