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A genetic approach in procedural content generation for platformer games level creation

机译:用于平台游戏关卡创建的过程内容生成中的遗传方法

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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 PCG. 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.
机译:在本文中,我们使用了一种遗传算法来生成和评估节奏,以创建2D跑步者平台游戏的等级。生成节奏后,我们使用了基于语法的方法来基于这些节奏生成几何。对于PCG领域的遗传算法,我们使用了一种新的适应度函数。这种方法还可以最大程度地减少必须手动创作的内容量。我们的结果表明,该方法可以产生各种级别,并且在两个级别之间控制难度,并且所有生成的级别都可以完全播放。我们认为,提出的方法可能适用于商业平台游戏。

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