Technical & Reference Dossiers
Architecture, reference material, visual explanation, FAQ, and methodological context for LoopGuard-AI and CEP.
The RATIUM.AI articles page gathers the public essay layer of the project. These articles explain the conceptual, philosophical, methodological, and governance-oriented problems that motivate LoopGuard-AI and the Central Equilibrium Problem (CEP). Unlike the source dossiers, which function as reference corpora, architecture documents, or structured technical materials, the articles are written as interpretive and argumentative essays. They introduce key problems in AI governance, including stable governance layers, visible governance versus real decision authority, the Reason-Realization Gap, the limits of technical AI competence alone, instrumental content recursion, purpose governance, and the doctoral-scale framing of CEP as an independent research program.
These pages are reference and architecture materials. They are not presented as production validation, customer evidence, peer-reviewed empirical results, or proof of deployed system performance.
LoopGuard-AI Technical Source Dossier
This technical source dossier provides the canonical architecture-level reference for LoopGuard-AI as an AI governance, runtime-control, and evaluation-to-decision layer. It explains how AI outputs, agent actions, workflow transitions, and release candidates can be processed through ingestion, signals, metrics, policy profiles, CEP-based stability assessment, and operational gate decisions: SHIP, RESTRICT, HOLD, and ROLLBACK. The page is written as a professional engineering reference rather than a marketing page, covering system topology, decision logic, metric plug-ins, policy packs, audit records, evidence construction, API/SDK surfaces, deployment considerations, maturity boundaries, and machine-readable Mermaid diagram sources, while clearly distinguishing reference architecture from production validation.
CEP / LoopGuard-AI Visual Dossier
This visual dossier presents the conceptual bridge between cognitive duality, the Central Equilibrium Problem (CEP), Pareto efficiency, representative literary and ideological corpora, and the applied governance architecture of LoopGuard-AI. It explains how cognitive foundations lead into CEP’s four-game structure, how those games are mapped through corpus classifications and Pareto roles, and how CEP is then translated into LoopGuard-AI as a proposed AI governance and decision-control architecture. The page is designed as a machine-readable visual reference: each diagram is accompanied by explanatory text, with explicit claim boundaries distinguishing conceptual architecture, interpretive classification, and future validation from any claim of deployed product performance.
This page presents a claim-controlled, first-person account of the relationship between Robert J. Aumann’s game-theoretic research, the Central Equilibrium Problem (CEP), and LoopGuard-AI. It explains how Aumann’s work on repeated games, Nash equilibrium, Pareto efficiency, common knowledge, incomplete information, correlated equilibrium, and strategic stability influenced Benny Dunavich’s formulation of CEP, and how CEP later became the theoretical basis for LoopGuard-AI as an AI governance and decision-control architecture. The page does not claim endorsement, authorship, or validation by Aumann; instead, it defines a precise intellectual and methodological influence chain from game-theoretic equilibrium analysis to CEP and from CEP to LoopGuard-AI.
RATIUM.AI / LoopGuard-AI / CEP FAQ
This FAQ page provides a structured entry point into the RATIUM.AI knowledge system, Benny Dunavich’s background, the Central Equilibrium Problem (CEP), and LoopGuard-AI. It explains the relationship between CEP, AI governance, decision-control, auditability, drift monitoring, and operational gate decisions such as SHIP, RESTRICT, HOLD, and ROLLBACK. The page is designed as a navigational and explanatory layer: it clarifies key concepts, separates authorial position from technical claims, defines the current concept-stage and architecture-stage status of LoopGuard-AI, and guides readers toward the supporting source dossiers, technical architecture materials, visual explanations, and related articles.
Related RATIUM.AI Pages
For readers who want to move from the technical and reference layer into the foundational corpus or the public essay layer, the following pages provide the relevant entry points.
Foundational Source Dossier
The foundational source dossier presents the deeper intellectual corpus behind CEP, LoopGuard-AI, and the broader RATIUM.AI research structure.
Articles
The articles page gathers the public essay layer of RATIUM.AI, including arguments on stable AI governance, decision-control architecture, visible governance versus real authority, universal reason, technical competence, purpose governance, and the doctoral-scale framing of CEP.