发表机构
National University of Singapore（新加坡国立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对人类难以理解国际象棋引擎走法背后策略的问题，提出策略语言化任务，设计了策略语言化流程与评估框架，实验表明自然语言可有效传达策略信息，还得出了关于评估、描述及评估方式的一些见解。
AI 中文摘要
长期以来，国际象棋引擎已具备超人的下棋实力。然而，即使是熟练的人类棋手也难以理解其走法建议背后的潜在策略。受此启发，我们提出了国际象棋策略语言化任务，即用自然语言描述国际象棋策略。我们设计了一个策略语言化流程和一个用于客观评估生成的策略描述的评估框架。实验表明，自然语言是向人类和语言模型棋手传达策略信息的有前景且可解释的媒介。我们还获得了其他有趣的见解，包括评估主线以外策略的重要性、纯基于概念描述的局限性以及依靠语言模型而非人类进行评估的局限性。
英文摘要
Chess engines have long achieved superhuman playing strength. However, the underlying strategy behind their move suggestions is difficult for human players, even skilled ones, to comprehend. Motivated by this, we propose the task of chess strategy verbalization, which is to describe chess strategies in natural language. We design (i) a pipeline for verbalizing strategies and (ii) an evaluation framework for objective evaluation of generated strategy descriptions. Our experiments show that natural language is a promising and interpretable medium for communicating strategic information to both human and LLM players. We glean additional interesting insights, including (a) the importance of evaluating strategies beyond the main line, (b) the limitations of pure concept-based descriptions, and (c) the limitations of relying on LLMs rather than humans for evaluation.
Comments21 pages, 13 figures
