Cognitive Insights and Stable Coalition Matching for Fostering Multi-Agent Cooperation

• URL: http://arxiv.org/abs/2405.18044v1
• Date: Tue, 28 May 2024 10:59:33 GMT
• Title: Cognitive Insights and Stable Coalition Matching for Fostering Multi-Agent Cooperation
• Authors: Jiaqi Shao, Tianjun Yuan, Tao Lin, Xuanyu Cao, Bing Luo,
• Abstract summary: We propose a novel matching coalition mechanism that leverages the strengths of agents with different ToM levels. Our work demonstrates the potential of leveraging ToM to create more sophisticated and human-like coordination strategies.
• Score: 6.536780912510439
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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