With growing interest in Procedural Content Generation (PCG) it becomes increasingly important to develop methods and tools for evaluating and comparing alternative systems. There is a particular lack regarding the evaluation of generative pipelines, where a set of generative systems work in series to make iterative changes to an artifact. We introduce a novel method called Generative Shift for evaluating the impact of individual stages in a PCG pipeline by quantifying the impact that a generative process has when it is applied to a pre-existing artifact. We explore this technique by applying it to a very rich dataset of Minecraft game maps produced by a set of alternative settlement generators developed as part of the Generative Design in Minecraft Competition (GDMC), all of which are designed to produce appropriate settlements for a pre-existing map. While this is an early exploration of this technique we find it to be a promising lens to apply to PCG evaluation, and we are optimistic about the potential of Generative Shift to be a domain-agnostic method for evaluating generative pipelines.

翻译：随着对程序化内容生成（PCG）兴趣的增长，开发评估与比较不同系统的方法和工具变得日益重要。当前尤其缺乏对生成管线的评估——即一系列生成系统串联工作，对同一工件进行迭代修改的过程。我们提出一种名为"生成偏移"（Generative Shift）的新方法，通过量化生成过程对既有工件的影响，评估PCG管线中各个阶段的作用。我们基于"我的世界"（Minecraft）游戏地图的丰富数据集探索该技术，这些地图由《我的世界》生成式设计竞赛（GDMC）中开发的多种替代性定居点生成器生成，所有生成器均旨在为既有地图生成合适的定居点。尽管这是对该技术的初步探索，但我们发现它为PCG评估提供了富有前景的视角，并乐观认为"生成偏移"有望成为评估生成管线的领域无关方法。