Artificial Leviathan: exploring social evolution of LLM agents through the lens of hobbesian social contract theory

Engineering notes

Key topics: autonomous driving, large language model. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

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Original abstract

Introduction The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science research at scale. Building upon prior explorations of LLM agent design, our work introduces a simulated agent society where complex social relationships dynamically form and evolve over time. Methods Agents are given psychological drives and placed in a sandbox survival environment. We conduct an evaluation of the agent society through the lens of Thomas Hobbes’s seminal Social Contract Theory (SCT), analyzing whether agents seek to escape a brutish “state of nature” by surrendering rights to an absolute sovereign in exchange for order and security. Results In our experiments, agents initially engage in unrestrained conflict, mirroring Hobbes’s depiction of the state of nature. However, as the simulation progresses, social contracts emerge, leading to the authorization of an absolute sovereign and the establishment of a peaceful commonwealth founded on mutual cooperation. Discussion The congruence between our LLM agent society’s evolutionary trajectory and Hobbes’s theoretical account indicates the capability of LLM’s to model intricate social dynamics that replicate forces which potentially shape human societies. By enabling insights into group behavior and emergent societal phenomena, LLM-driven multi-agent simulations hold potential for advancing our understanding of social structures, group dynamics, and complex human systems.

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