This paper aims to develop a new attribution method to explain the conflict between individual variables' attributions and their coalition's attribution from a fully new perspective. First, we find that the Shapley value can be reformulated as the allocation of Harsanyi interactions encoded by the AI model. Second, based the re-alloction of interactions, we extend the Shapley value to the attribution of coalitions. Third we ective. We derive the fundamental mechanism behind the conflict. This conflict come from the interaction containing partial variables in their coalition.

翻译：本文旨在从一个全新的视角发展一种归因方法，以解释单个变量的归因与其所在联盟的归因之间的冲突。首先，我们发现沙普利值可以重新表述为人工智能模型编码的哈萨尼交互分配的产物。其次，基于交互的重新分配，我们将沙普利值扩展到联盟的归因。第三，我们推导出冲突背后的基本机制。这一冲突源于联盟中包含部分变量的交互作用。