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Automatic evolution of programs for procedural generation of terrains for video games

机译:用于程序生成地形的视频游戏程序的自动演化

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Nowadays the video game industry is facing a big challenge to keep costs under control as games become bigger and more complex. Creation of game content, such as character models, maps, levels, textures, sound effects and so on, represent a big slice of total game production cost. Hence, the video game industry is increasingly turning to procedural content generation to amplify the cost-effectiveness of the efforts of video game designers. However, procedural methods for automated content generation are difficult to create and parametrize. In this work we study a genetic programming-based procedural content technique to generate procedural terrains that do not require parametrization, thus, allowing to save time and help reducing production costs. Generated procedural terrains present aesthetic appeal; however, unlike most techniques involving aesthetic, our approach does not require a human to perform the evaluation. Instead, the search is guided by the weighted sum of two morphological metrics: terrain accessibility and obstacle edge length. The combination of the two metrics allowed us to find a wide range of fit terrains that present more scattered obstacles in different locations than our previous approach with a single metric. Procedural terrains produced by this technique are already in use in a real video game.
机译:如今,随着游戏变得越来越大,越来越复杂,视频游戏产业面临着巨大的挑战,如何控制成本。游戏内容的创建(例如角色模型,地图,级别,纹理,声音效果等)占游戏总生产成本的很大一部分。因此,视频游戏行业越来越多地转向过程性内容生成,以扩大视频游戏设计师的工作的成本效益。但是,用于自动内容生成的过程方法很难创建和参数化。在这项工作中,我们研究了一种基于遗传程序的程序内容技术,以生成不需要参数化的程序地形,从而节省了时间并有助于降低生产成本。生成的过程地形具有美学吸引力;但是,与大多数涉及美学的技术不同,我们的方法不需要人工来进行评估。取而代之的是,搜索是由两个形态学指标的加权和指导的:地形可及性和障碍物边缘长度。这两个指标的结合使我们能够找到各种适合的地形,这些地形比我们以前使用单个指标的方法在不同位置呈现更多的分散障碍。通过这种技术产生的程序性地形已经在实际的视频游戏中使用。

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