A Genetic Approach in Procedural Content Generation for Platformer Games Level Creation

被引:0
|
作者
Moghadam, Arman Balali [1 ]
Rafsanjani, Marjan Kuchaki [1 ]
机构
[1] Shahid Bahonar Univ Kerman, Dept Comp Sci., Kerman, Iran
关键词
artificial intelligence; games; level design; procedural content generation (peG); genetic algorithm; 2D platformers;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this article we used a genetic algorithm approach for generating and evaluating rhythms for creating levels of 2D runner platformer games. After generating rhythms, we used a grammar based approach to generate geometry based on these rhythms. We used a novel fitness function for the genetic algorithm in the area of peG. This approach also minimizes the amount of the content that must be manually authored. Our results show that this method can produce a variety of levels with controlled difficulty between two levels and all generated levels are fully playable. We believe that the presented method is potentially applicable to commercial platformer games.
引用
收藏
页码:141 / 146
页数:6
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