  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. Agents are imbued with 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). We analyze whether, as the theory postulates, agents
seek to escape a brutish "state of nature" by surrendering rights to an
absolute sovereign in exchange for order and security. Our experiments unveil
an alignment: Initially, agents 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. This congruence between our LLM agent society's
evolutionary trajectory and Hobbes's theoretical account indicates LLMs'
capability to model intricate social dynamics and potentially replicate forces
that shape human societies. By enabling such insights into group behavior and
emergent societal phenomena, LLM-driven multi-agent simulations, while unable
to simulate all the nuances of human behavior, may hold potential for advancing
our understanding of social structures, group dynamics, and complex human
systems.
