Joint Lyapunov Certificates for K-Agent Generative AI Governance: Stochastic Stability, Emergent Ensemble Risk, and Zero-Knowledge Governance Attestation

What the math gives to ML

The paper provides a directly implementable spectral stability certificate for coupled learning agents, showing that ensemble coupling can destabilize a system even when every individual model is stable. The transferable asset is the identification of the most negative eigenvalue of the interaction matrix as the dangerous mode, together with a conservative Cholesky-checkable certificate based on the symmetric part of the coupling matrix. A practical neural-network adaptation is to couple adapter, optimizer, or recurrent-state updates across model replicas while constraining the coupling strength below the certified spectral threshold.