Evolving Interpretable Constitutions for Multi-Agent Coordination

Understand

Constitutional AI has focused on single-model alignment using fixed principles.

• However, multi-agent systems create novel alignment challenges through emergent social dynamics.
• We present Constitutional Evolution, a framework for automatically discovering behavioral norms in multi-agent LLM systems.
• Using a grid-world simulation with survival pressure, we study the tension between individual and collective welfare, quantified via a Societal Stability Score S in [0,1] that combines productivity, survival, and conflict metrics.