Procedural content generation (PCG) for games has existed since the 1980s and is becoming increasingly important for creating game worlds, backstory, and characters across many genres, in particular, open-world games, such as Minecraft (2011) and No Man's Sky (2016). A particular challenge faced by such games is that the content and/or gameplay may become repetitive. Puzzles constitute an effective technique for improving gameplay by offering players interesting problems to solve, but the use of PCG for generating puzzles has been limited compared with its use for other game elements, and efforts have focused mainly on games that are strictly puzzle games, rather than creating puzzles to be incorporated into other genres. Nevertheless, a significant body of work exists, which allows puzzles of different types to be generated algorithmically, and there is scope for much more research into this area. This paper presents a detailed survey of existing work in PCG for puzzles, reviewing 32 methods within 11 categories of puzzles. For the purpose of analysis, this paper identifies a total of seven salient characteristics related to the methods, which are used to show commonalities and differences between techniques and to chart promising areas for future research.

中文翻译：

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程序拼图生成：调查

游戏的程序化内容生成 (PCG) 自 1980 年代就已存在，并且对于创建跨多种类型的游戏世界、背景故事和角色变得越来越重要，尤其是开放世界游戏，例如 Minecraft（2011）和 No Man's Sky（ 2016）。此类游戏面临的一个特殊挑战是内容和/或游戏玩法可能会变得重复。拼图是一种通过为玩家提供有趣的问题来改善游戏玩法的有效技术，但与用于其他游戏元素相比，PCG 用于生成拼图的使用受到限制，并且努力主要集中在严格意义上的益智游戏上，而不是而不是创造谜题以融入其他类型。尽管如此，仍有大量工作可以通过算法生成不同类型的谜题，这个领域还有更多的研究空间。本文详细介绍了 PCG 中现有的谜题工作，回顾了 11 类谜题中的 32 种方法。出于分析的目的，本文共确定了与这些方法相关的七个显着特征，用于显示技术之间的共性和差异，并为未来研究绘制有前景的领域。