Artificial Intelligence Based Game Levelling
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Date
Authors
Cetin, Meric
Sarica, Yunus
Journal Title
Journal ISSN
Volume Title
Publisher
Open Access Color
GOLD
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
The applications of artificial intelligence (AI), which is a comprehensive information technology, have been closely related to game technologies. Today, artificial intelligence-based game development applications are increasing their popularity day by day. In this study, the levelling process of a 2-dimensional (2D) platform game has been 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.
Description
Keywords
Yapay Zeka, Artificial Intelligence, Artificial Intelligence;Difficulty Adjustment;Content Generation;k-Nearest Neighbor;Random Forest;Artificial Neural Networks, 004
Fields of Science
0301 basic medicine, 0303 health sciences, 03 medical and health sciences
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
N/A
Volume
8
Issue
2
Start Page
147
End Page
153
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Mendeley Readers : 6



