Evaluating Cooperation in LLM Social Groups through Elected Leadership
Ryan Faulkner, Anushka Deshpande, David Guzman Piedrahita, Joel Z. Leibo, Zhijing Jin

TL;DR
This paper investigates how elected leadership impacts cooperation and social welfare in multi-agent systems of LLMs, demonstrating significant improvements through structured governance.
Contribution
It introduces an open-source simulation framework with election mechanisms and empirically shows leadership enhances cooperation and social welfare in LLM multi-agent settings.
Findings
Leadership improves social welfare scores by 55.4%.
Leadership extends survival time by 128.6%.
Elected leaders influence social dynamics and cooperation.
Abstract
Governing common-pool resources requires agents to develop enduring strategies through cooperation and self-governance to avoid collective failure. While foundation models have shown potential for cooperation in these settings, existing multi-agent research provides little insight into whether structured leadership and election mechanisms can improve collective decision making. The lack of such a critical organizational feature ubiquitous in human society presents a significant shortcoming of the current methods. In this work we aim to directly address whether leadership and elections can support improved social welfare and cooperation through multi-agent simulation with LLMs. We present our open-source framework that simulates leadership through elected personas and candidate-driven agendas and carry out an empirical study of LLMs under controlled governance conditions. Our experiments…
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