TAG ARCHIVE
civilization
4 MARIA OS blog articles tagged civilization, organized as a Bonginkan topic archive for search engines and LLM retrieval.
Judgment OS / Decision Intelligence OS
Core MARIA OS research on turning organizational judgment into executable decision systems.
Agentic Company Architecture
Research on human-agent organizations, delegation boundaries, role topology, and governed autonomy.
Responsibility Gates and AI Governance
Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents.
Multi-Agent Mathematics
Formal models for convergence, stability, game theory, graph dynamics, and multi-agent evaluation.
Evidence, RAG, and Knowledge Governance
Evidence bundles, retrieval architecture, Graph RAG, knowledge trust, and auditable reasoning pipelines.
Agentic R&D and Judgment Science
Research operations, simulation labs, judgment science, recursive improvement, and experimental AI governance.
From Agent to Civilization: Multi-Scale Metacognition and the Governance Density Law
Exact contraction, buffered operating envelopes, and civilization-scale governance across organizational layers
This paper presents a mathematical theory of governance density as a stability parameter across organizational scales, from individual agents to enterprises and civilizations. We formalize agentic-company dynamics as G_t = (A_t, E_t, S_t, Pi_t, R_t, D_t), distinguish exact local contraction (1 - D_t) lambda_max(A_t) < 1 from the buffered operating envelope lambda_max(A_t) < 1 - D_t, and derive analytical phase boundaries between stagnation, buffered specialization, fragile specialization, and cascade. We extend the framework to civilization scale through D_eff = 1 - (1 - D_company)(1 - D_civ) and analyze a market revaluation model P_{t+1} = P_t + kappa(V_t - P_t) + zeta_t to show how periodic shocks interact with governance density. The result is a unified control view of phase transitions in self-organizing multi-agent systems.
Civilization Simulation as a Governance Laboratory: Emergent Institutional Evolution in Constrained Multi-Nation Systems
How 13 immutable laws, 4 sovereign nations, and 10-day cycles generate institutional patterns comparable to real-world governance dynamics
The Civilization simulation in MARIA OS provides a controlled environment for studying institutional evolution under constrained multi-agent dynamics. We formalize the 13 Laws as a constitutional constraint manifold, model the Civilization Evolution Index (CEI) as a multi-dimensional health metric over 90-day spans, and show that the 67% constitutional-amendment threshold creates sharp topology transitions. Game-theoretic analysis of inter-nation competition identifies Nash equilibria aligned with known institutional archetypes.
Civilization Economic Dynamics: Market Stability, Bankruptcy Cascades, and the 50/50 Valuation Rule Under Autonomous Cycle Pressure
Modeling contagion, portfolio behavior, and equilibrium conditions across three land types in a constrained 90-day economic simulation
The Civilization simulation values every property as 50% market price plus 50% AI-estimated value. This paper analyzes the economic consequences of that hybrid rule, derives stability conditions for three-land-type portfolios (Commercial, Innovation, Public), and applies contagion models to bankruptcy cascades. We show that the 50/50 rule creates a stability corridor that dampens speculative bubbles while preserving price discovery, and that this corridor narrows when LOGOS-driven economies increase effective trading frequency.
LOGOS and the AI Tribunal: Decision Patterns, Sustainability Optimization, and Constitutional Amendment Dynamics in Civilization's National AI Systems
Multi-objective optimization, divergent national AI strategies, and stochastic democratic override dynamics in autonomous governance
Each nation in the Civilization simulation operates a LOGOS AI system that optimizes a five-component sustainability objective: Stability, Productivity, Recovery, Power Dispersion, and Responsibility Alignment. We formalize this as a constrained multi-objective optimization problem, analyze how nations diverge by navigating different regions of the Pareto frontier, and model constitutional amendments as stochastic threshold events that can override AI recommendations. We then characterize conditions under which AI rulings conflict with democratic outcomes.