Recent advances in game informatics have enabled us to find strong strategies across a diverse range of games. However, these strategies are usually difficult for humans to interpret. On the other hand, research in Explainable Artificial Intelligence (XAI) has seen a notable surge in scholarly activity. Interpreting strong or near-optimal strategies or the game itself can provide valuable insights. In this paper, we propose two methods to quantify the feature importance using Shapley values: one for the game itself and another for individual AIs. We empirically show that our proposed methods yield intuitive explanations that resonate with and augment human understanding.

翻译：近期游戏信息学的进展使我们能够在各类游戏中发现强大的策略。然而，这些策略通常难以被人类解读。与此同时，可解释人工智能（XAI）领域的研究活动显著增加。解读强大或近乎最优的策略乃至游戏本身，可以提供宝贵的洞见。本文提出两种基于Shapley值量化特征重要性的方法：一种用于游戏本身，另一种用于个体人工智能。我们通过实验表明，所提出的方法能够生成符合并增强人类理解的直观解释。