Cognitive abilities, such as Theory of Mind (ToM), play a vital role in facilitating cooperation in human social interactions. However, our study reveals that agents with higher ToM abilities may not necessarily exhibit better cooperative behavior compared to those with lower ToM abilities. To address this challenge, we propose a novel matching coalition mechanism that leverages the strengths of agents with different ToM levels by explicitly considering belief alignment and specialized abilities when forming coalitions. Our proposed matching algorithm seeks to find stable coalitions that maximize the potential for cooperative behavior and ensure long-term viability. By incorporating cognitive insights into the design of multi-agent systems, our work demonstrates the potential of leveraging ToM to create more sophisticated and human-like coordination strategies that foster cooperation and improve overall system performance.

翻译：认知能力，如心智理论（ToM），在促进人类社会互动中的合作方面起着至关重要的作用。然而，我们的研究表明，与ToM能力较低的智能体相比，具有较高ToM能力的智能体未必表现出更好的合作行为。为了应对这一挑战，我们提出了一种新颖的匹配联盟机制，该机制在组建联盟时，通过明确考虑信念对齐和专业能力，来利用具有不同ToM水平智能体的优势。我们提出的匹配算法旨在寻找能够最大化合作行为潜力并确保长期可行性的稳定联盟。通过将认知洞察融入多智能体系统的设计中，我们的工作展示了利用ToM来创建更复杂、更类人的协调策略的潜力，这些策略能够促进合作并提高整体系统性能。