用数学方法系统化设计逻辑谜题规则,让电脑也能自动造新谜题。
Mathematical Definition and Systematization of Puzzle Rules
- 构建网格元素与关系的数学框架,支持规则逐步生成。
- 成功形式化了四分之一已知谜题规则,包括数独和密道连接。
- 为智能造题、教育游戏和创造性计算提供新工具。
尽管逻辑谜题长期激发人们的解题与批判性思维,但新规则的创作仍依赖非系统化的经验方法。铅笔谜题如密道连接(Slitherlink)和数独(Sudoku)是其中典型代表,以组合逻辑与空间推理为核心挑战。尽管已有大量关于求解技术和自动生成问题的研究,但统一的规则设计框架仍缺失。本文提出一种数学框架,用于定义与系统化铅笔谜题规则。该框架形式化了网格元素、其位置关系及迭代组合操作,支持结构的增量构建,构成谜题规则的基础。同时,建立形式化约束与域描述方法,确保规则可解性与一致性。应用该框架,我们成功形式化了多个知名尼科利谜题规则,涵盖约四分之一现有谜题。结果验证了框架在系统化与创新规则设计中的潜力,为自动化规则生成开辟路径。通过为谜题规则创建数学基础,该工作推动计算机(尤其是结合AI)根据玩家偏好设计新型谜题,拓展谜题多样性。此外,该研究展示了数学框架如何连接娱乐数学与算法设计,为基于逻辑的系统探索提供工具,潜在应用于教育游戏设计、个性化学习与计算创造力领域。
原文摘要 · Abstract (English)
While logic puzzles have engaged individuals through problem-solving and critical thinking, the creation of new puzzle rules has largely relied on ad-hoc processes. Pencil puzzles, such as Slitherlink and Sudoku, represent a prominent subset of these games, celebrated for their intellectual challenges rooted in combinatorial logic and spatial reasoning. Despite extensive research into solving techniques and automated problem generation, a unified framework for systematic and scalable rule design has been lacking. Here, we introduce a mathematical framework for defining and systematizing pencil puzzle rules. This framework formalizes grid elements, their positional relationships, and iterative composition operations, allowing for the incremental construction of structures that form the basis of puzzle rules. Furthermore, we establish a formal method to describe constraints and domains for each structure, ensuring solvability and coherence. Applying this framework, we successfully formalized the rules of well-known Nikoli puzzles, including Slitherlink and Sudoku, demonstrating the formal representation of a significant portion (approximately one-fourth) of existing puzzles. These results validate the potential of the framework to systematize and innovate puzzle rule design, establishing a pathway to automated rule generation. By providing a mathematical foundation for puzzle rule creation, this framework opens avenues for computers, potentially enhanced by AI, to design novel puzzle rules tailored to player preferences, expanding the scope of puzzle diversity. Beyond its direct application to pencil puzzles, this work illustrates how mathematical frameworks can bridge recreational mathematics and algorithmic design, offering tools for broader exploration in logic-based systems, with potential applications in educational game design, personalized learning, and computational creativity.
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