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March 14, 20260 citationsOpen Access

Recursive Equilibrium: A Unified Framework For Stability in AI Systems

Recursive Equilibrium v1.2: A Unified Framework for Epistemic, Ethical, Semantic & Relational-Structure Stability in AI Systems

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KLKon Lionis

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Overview

Framework proposes a unified structure for AI stability in various domains, suggesting coordinated behaviors.

Key Points

  • The aim is to develop a holistic framework that integrates multiple stability criteria for AI systems.
  • Introduced Recursive Equilibrium as a framework for AI stability.
  • Proposed coupling of four structures: epistemic calibration, ethical reflexivity, semantic coherence, and relational-structure preservation.
  • Illustrated multi-dimensional interactions through a machine learning-native translation.
  • Hypothesized that stability in one domain could influence others via feedback mechanisms.
  • Proposed that the framework can support testable predictions regarding AI stability.
  • Identified key open questions about validation and implementation across coupled layers.

Cite This Study

Kon Lionis (2025) studied this question.

synapsesocial.com/papers/69b4fb8db39f7826a300bcf3https://doi.org/10.5281/zenodo.18975175
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