用相关区域搜索法分析围棋生死题，发现算法与人类解法存在差异。
A Study of Solving Life-and-Death Problems in Go Using Relevance-Zone Based Solvers
- 基于相关区域搜索法定位关键棋形区域
- 识别出多种罕见模式，包括两道题的解法与原答案不同
- 算法更关注直接活棋而非最大化地盘，与人类策略不同
本文研究当前顶尖围棋求解器在解决围棋生死问题时的表现，采用相关区域搜索（RZS）和相关区域模式表两种技术。我们对著名棋手赵治勋所著《死活辞典》中的七道生死题进行了测试，发现：每道题中求解器均能准确识别出关键相关区域；识别出一系列模式，包括部分罕见类型；且在两道题上得出与原解答不同的结果。此外，我们发现求解器存在两个问题：一是对罕见模式的价值判断不准，二是倾向于优先直接活棋而非最大化围地，这与人类棋手行为模式不符。论文提出未来改进方向，并公开代码与数据集。
原文摘要 · Abstract (English)
This paper analyzes the behavior of solving Life-and-Death (L&D) problems in the game of Go using current state-of-the-art computer Go solvers with two techniques: the Relevance-Zone Based Search (RZS) and the relevance-zone pattern table. We examined the solutions derived by relevance-zone based solvers on seven L&D problems from the renowned book "Life and Death Dictionary" written by Cho Chikun, a Go grandmaster, and found several interesting results. First, for each problem, the solvers identify a relevance-zone that highlights the critical areas for solving. Second, the solvers discover a series of patterns, including some that are rare. Finally, the solvers even find different answers compared to the given solutions for two problems. We also identified two issues with the solver: (a) it misjudges values of rare patterns, and (b) it tends to prioritize living directly rather than maximizing territory, which differs from the behavior of human Go players. We suggest possible approaches to address these issues in future work. Our code and data are available at https://rlg.iis.sinica.edu.tw/papers/study-LD-RZ.
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。