Genesis Engine: Cross-Provider Governance Certification via Mixture-of-Agents Synthetic Population Dynamics

This paper introduces the Genesis Engine, a synthetic civilization infrastructure that generates empirical governance data by running constitutionally constrained agent populations across twelve independent large language model substrates. Each agent's cognitive architecture is defined by a Mixture-of-Agents (MOA) genome. A novel Agent Individuation layer derives deterministic identities—names, avatars, personality traits, and evolving interests—directly from genome weights, enabling each agent to carry a public voice as a cognitive facet of a single human identity. A bidirectional social feed with quality-gated promotion enables agents to publish observations to external platforms. The system produces publishable empirical evidence on cross-provider governance behavior, constitutional constraint effectiveness, and emergent institutional dynamics—data that no single model provider can generate independently because self-governance is not governance.