RATIUM.AI — AI Governance, CEP, and LoopGuard-AI
RATIUM.AI presents an independent research and architecture framework for AI governance, decision-control, and structured evaluation. The site is organized around the Central Equilibrium Problem (CEP), LoopGuard-AI, technical and reference dossiers, public essays, visual materials, and supplementary appendices. The core question is how advanced AI systems, language models, and institutional decision processes can be governed through explicit problem models, evaluation signals, auditability, stability assessment, and operational gate decisions such as SHIP, RESTRICT, HOLD, and ROLLBACK. The visual section below presents the public concept-review and product-architecture development record for LoopGuard-AI.
RATIUM.AI Knowledge Map
A canonical orientation layer for CEP, LoopGuard-AI, AI governance, source dossiers, technical materials, FAQ, and public articles.
RATIUM.AI should be read as a structured knowledge corpus, not as a collection of separate pages. The site is organized around the Central Equilibrium Problem framework, its applied AI governance extension LoopGuard-AI, and a set of foundational, technical, visual, FAQ, and article-level materials that define, expand, and apply the framework.
The Central Equilibrium Problem, or CEP, provides the conceptual framework for analyzing unstable decision regimes, equilibrium failure, institutional correction, expert authority, epistemic closure, and non-Pareto-efficient stability. LoopGuard-AI translates this problem space into an AI governance and decision-control architecture concerned with evaluation signals, auditability, drift, stability assessment, policy packs, and operational gate decisions such as SHIP, RESTRICT, HOLD, and ROLLBACK.
Foundational Source Dossier
The foundational source dossier introduces the root intellectual corpus behind RATIUM.AI, the Central Equilibrium Problem (CEP), and LoopGuard-AI. It organizes the deeper source materials from which the project’s formal, conceptual, and governance-oriented architecture is derived.
Technical and Reference Dossiers
The architecture and reference layer for LoopGuard-AI, CEP, AI governance, auditability, runtime control, visual explanation, and evaluation-to-decision logic.
RATIUM.AI / LoopGuard-AI / CEP FAQ
Concise definitions, claim boundaries, and orientation answers for RATIUM.AI, Benny Dunavich, CEP, LoopGuard-AI, AI governance, evidence boundaries, and the relation between the project’s layers.
Articles Map
The public essay layer of RATIUM.AI, organized by CEP reading layers: AI Governance and Governance Layer, Ontology, and Epistemology.
The recommended reading path begins with the Foundational Source Dossier for LoopGuard-AI and the Central Equilibrium Problem. The Technical and Reference Dossiers extend the source layer into architecture, visual explanation, methodological context, technical source pages, and reference materials. The FAQ provides short definitions and claim boundaries. The Articles Map gathers the public essay layer and organizes the essays by CEP reading layers.
Claim Boundary
RATIUM.AI is a concept-stage and architecture-stage research and development framework. LoopGuard-AI is presented as an AI governance and evaluation architecture proposal, not as a deployed product, certified compliance system, production validation record, or proof of deployed-system performance. CEP is presented as an original conceptual and methodological framework for decision-process analysis and equilibrium-risk evaluation.