Epistemically-Governed Reasoning Architecture (EGRA)
Creators: name: Ivliev, Ihor
name: GenAI, LLMs
Publisher: name: Zenodo
Year: 2025
Subjects: subject: EGRA
subject: Epistemic Governance
subject: FCJF
subject: HGA
subject: CBSR
subject: 5D Intrinsic Maturity Profile
subject: PCCMGA Pillars
subject: MDBA
subject: GVG
subject: VPO
subject: RJM
subject: JSM
subject: VSA
subject: MVL
subject: CEP
subject: TUR
subject: Reasoning Unit
subject: Maturity (AI)
subject: Justification Record
subject: Constraint Management
subject: Constraint Supremacy
subject: Audit-First Design
subject: Epistemic Lifecycle
subject: Integrity Gateway
subject: Operationalized Humility
subject: Meta-Governance
subject: Justification-First Architecture
subject: Governed Reasoning
subject: Self-Auditing AI (Conceptual)
subject: Conceptual Architecture
subject: Reference Architecture
subject: Cognitive Architecture (Conceptual)
subject: Trustworthy AI
subject: AI Safety
subject: AI Alignment
subject: AI Governance
subject: AI Ethics
subject: Explainable AI (XAI)
subject: AI Auditing
subject: Auditability (AI)
subject: AI Accountability
subject: Accountable AI
subject: Verifiable AI
subject: Responsible AI
subject: Artificial intelligence
subject: Artificial Intelligence
subject: Artificial Intelligence/standards
subject: Artificial Intelligence/trends
subject: Artificial Intelligence/classification
subject: Artificial Intelligence/ethics
subject: Artificial Intelligence
subject: High-Stakes AI
subject: AI Risk Management
subject: Computational Epistemology
subject: Epistemology
subject: Knowledge Representation
subject: Formal Methods (AI Governance)
subject: Transparency (AI)
subject: Ethical principles
subject: Ethics
subject: Ethics
subject: Ethics
subject: Metadata
subject: Metadata/ethics
subject: Metadata/standards
subject: Metadata/trends
subject: Metadata parameters
subject: Machine learning
subject: Machine Learning
subject: Machine Learning/ethics
subject: Machine Learning/standards
subject: Risk
subject: Risk
subject: Cognitive psychology
subject: Cognition
subject: Cognitive neuroscience
subject: Safety
subject: Safety
subject: Knowledge Representation and Reasoning
subject: Cognitive Systems/Architecture
subject: Trust
subject: Governance
subject: Policy
subject: Policy
subject: Culturally Appropriate Technology
subject: Culturally Appropriate Technology/ethics
subject: Culturally Appropriate Technology/methods
subject: Culturally Appropriate Technology/trends
subject: Information Technology/ethics
subject: Computer Systems
subject: Computer Systems/ethics
subject: System software
subject: System thinking

description: This paper introduces the Epistemically-Governed Reasoning Architecture (EGRA), a conceptual framework designed to address critical challenges in achieving verifiable trustworthiness, accountability, and justifiable reasoning in advanced AI systems, particularly for high-stakes applications. EGRA's core proposition is the embedding of explicit epistemic governance – rules and mechanisms derived from principles of justification, evidence, uncertainty, and rationality – directly into the AI's operational structure.

The architecture is guided by six core value principles – Purity, Clarity, Cause-and-Effect, Modularity, Grounding, and Adaptability (PCCMGA) – which serve as the normative compass for design and runtime governance. Key architectural contributions include: the Formalized Calibration Justification Framework (FCJF) for rigorous meta-governance of the architecture itself; the Hierarchical Governance Architecture (HGA) providing multi-layered runtime control; the Comprehensive Belief State Representation (CBSR) integrating rich metadata including the 5D Intrinsic Maturity Profile and Typed Uncertainty Representation (TUR); dedicated mechanisms for validation assessment (MDBA) and orchestration (GVG/VPO); an Audit-First Design operationalized via the Runtime Justification Manager (RJM) for immutable justification logging; principled change management through Validated System Adaptation (VSA); process health monitoring via the Meta-Validation Loop (MVL); and critical incident handling via the Critical Event Protocol (CEP).

EGRA aims to foster demonstrably justifiable, robust, and ethically-aligned AI by structurally integrating these validation and governance mechanisms. It is presented as an implementation-agnostic conceptual blueprint and reference architecture, explicitly acknowledging areas requiring significant further research (e.g., metric instantiation, FCJF operationalization) and empirical validation to realize its potential.