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June 10, 20260 citationsOpen Access

A Simulation-Constrained Dynamic Architecture for Governance Stability

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QYQianJun Yu

Key Points

  • The aim is to develop a modular architecture that enhances governance stability by modeling trust and disturbances.
  • Evaluated through over 400 simulation runs across various network topologies (ring, mesh, star, federation).
  • Incorporated nine interdependent components affecting trust propagation and governance dynamics.
  • Introduced mechanisms for stress detection, redundancy constraints, and explicit failure modes.
  • Star topologies with specific hub configurations were found to generate unstable ignition dynamics (disallowed in current models).
  • Federation topologies require a special cluster-variance monitoring mechanism, deviating from standard detection methods.
  • The architecture offers flexible calibration parameters for practical implementations.

Abstract

This paper presents a simulation-constrained dynamic architecture for governance stability developed within the broader System of Eternity (SOE) research program. The architecture models institutional trust as a continuous variable evolving under disturbance, governance capacity, cognitive distortion, identity coherence, and adaptive recovery dynamics. The framework specifies nine interdependent architectural components governing trust propagation, disturbance buffering, topology-conditioned stress detection, governance coupling, stability locking, recovery activation, and meta-governance escalation. The architecture was evaluated through more than 400 simulation runs across ring, mesh, star, and federation network topologies. Simulation results produce a set of conditional structural constraints within the tested parameter regimes. Star topologies with one or two hubs generate sustained ignition dynamics and are treated as disallowed deployment configurations under current assumptions, while federation topologies avoid sustained ignition but require a distinct cluster-variance monitoring mechanism rather than standard network-threshold detection. The paper additionally introduces:- topology-conditioned stress detection,- hub redundancy constraints,- asynchronous trust-update coordination,- heterogeneous node abstractions for human, institutional, and AI governance participants,- explicit architectural assumptions and failure modes,- and open calibration parameters for deployment-specific implementation. The architecture is intended as a modular governance-stability framework for simulation, critique, calibration, and extension rather than a finalized universal governance model.

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Cite This Study

QianJun Yu (2026) studied this question.

synapsesocial.com/papers/6a28fe9f6f82f25be989bd4fhttps://doi.org/10.5281/zenodo.20586843
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