In this paper we describe a hierarchical method for procedurally generating 2D game maps using multi-dimensional Markov chains (MdMCs). Our method takes a collection of 2D game maps, breaks them into small chunks and performs clustering to find a set of chunks that correspond to high-level structures (high-level tiles) in the training maps. This set of high-level tiles is then used to re-represent the training maps, and to fit two sets of MdMC models: a high-level model captures the distribution of high-level tiles in the map, and a set of low-level models capture the internal structure of each high-level tile. These two sets of models can then be used to hierarchically generate new maps. We test our approach using two classic games, Super Mario Bros. and Loderunner, and compare the results against other existing map generators.
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机译：在本文中，我们描述了一种使用多维马尔可夫链（MDMC）的程序性地生成2D游戏映射的分层方法。我们的方法采用了一系列2D游戏映射，将它们分解为小块并执行群集以查找一组对应于培训地图中的高级结构（高级瓷砖）的块。然后使用这组高级瓦片重新代表培训贴图，并适合两组MDMC模型：高级模型捕获地图中的高级瓦片的分布，以及一组低级别级别模型捕获每个高级瓦片的内部结构。然后可以使用这两组模型来分层生成新的地图。我们使用两个经典游戏，Super Mario Bros.和Loderunner测试我们的方法，并将结果与其他现有地图生成器进行比较。
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