用交互可视化展示8数码谜题全部18万状态，助学生理解搜索算法
Full State-Space Visualisation of the 8-Puzzle: Feasibility, Design, and Educational Use
- 通过Unity和GPU技术实现18万状态的实时可视化
- 支持搜索算法逐步执行与不同策略对比
- 适合高校人工智能课程教学使用
搜索算法是人工智能教育的基础内容，但即使简单的8数码谜题也产生庞大的状态空间（181,440个状态），挑战学习者的认知建模能力。本文提出一个交互式学习系统，展示了完整可视化该问题可达状态空间的技术可行性，并将抽象图结构与具体拼图操作紧密结合。系统基于Unity和现代GPU渲染技术，支持全局结构实时探索、搜索算法分步执行，以及不同策略在同一空间中的直接对比。我们描述了系统设计、可视化布局及教育应用，并报告了在大学不同年级学生中开展的课堂部署与试点研究结果。总体表明，全状态空间可视化在技术上可行且对理解该经典问题域中的搜索行为具有教育价值。
原文摘要 · Abstract (English)
Search algorithms are a foundational topic in artificial intelligence education, yet even simple domains can generate large state spaces that challenge learners' ability to form accurate mental models. This paper presents an interactive learning system that demonstrates the feasibility of visualising the entire reachable state space of the 8-puzzle (181,440 states), while tightly coupling abstract graph structure with concrete puzzle manipulation. Built using Unity and modern GPU-based rendering techniques, the system enables real-time exploration of global structure, step-by-step execution of search algorithms, and direct comparison of how different strategies traverse the same space. We describe the system's design, visualisation layouts, and educational use, reporting findings from an initial classroom deployment and pilot study with students at different levels of university education. Overall, the results indicate that full state-space visualisation is both technically feasible and educationally valuable for supporting conceptual understanding of search behaviour within this canonical problem domain.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。