Ontological Foundations of Epistemic Stability under Informational Constraints
Abstract
This document provides the formal theoretical foundation for the Hybrid Meta-Controller (HMC) architecture introduced in the main paper “Entropy-Induced Collapse in Learned Decision Policies under Partial Observability and Architectural Mitigation”. While the primary work focuses on empirical validation and software engineering, this supplement establishes the ontological and informational guarantees underlying the proposed architecture. We show that policy collapse under partial observability is not a failure of training or optimization, but an informational inevitability governed by a critical limit, denoted αcrit. Under a minimal set of decision-theoretic axioms, we establish that asymptotic stability cannot be ensured by purely inductive policies, and requires a hybrid decision architecture capable of undergoing an epistemic phase transition between inductive and deductive regimes. This work studies an information-theoretic constraint governing epistemic stability under partial observability, hereafter referred to as the "Epistemic Stability Principle (ESP).”
Fields of Study & Subjects
Advanced Software Engineering Methodologies
Formal Methods in Verification
Reinforcement Learning in Robotics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 6 January 2026