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

Quantifying Feature Importance of Games and Strategies via Shapley Values