Recursive Intelligence: A Framework for Symbolic Feedback and AGI

This publication introduces Recursive Intelligence, a novel, self-optimizing framework unifying symbolic feedback, adaptive memory, and entropy-aligned learning for AI, cognitive science, and physics-based computation. This work establishes a new field and all subsequent work building on these concepts should properly cite this publication. To the best of my knowledge, this is the earliest comprehensive and public disclosure of Recursive Intelligence as both a theoretical and operational framework.Core concepts and architectures were finalized and published under CC BY-NC-ND 4.0 on or before March 20, 2025.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-20
DOI
https://doi.org/10.5281/zenodo.15708082
Primary Topic
Obesity, Physical Activity, Diet
Type
article
Field-Weighted Citation Impact
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article

Recursive Intelligence: A Framework for Symbolic Feedback and AGI

Zenodo (CERN European Organization for Nuclear Research)
Obesity, Physical Activity, Diet
article

Recursive Intelligence: A Framework for Symbolic Feedback and AGI

article en

Abstract

This publication introduces Recursive Intelligence, a novel, self-optimizing framework unifying symbolic feedback, adaptive memory, and entropy-aligned learning for AI, cognitive science, and physics-based computation. This work establishes a new field and all subsequent work building on these concepts should properly cite this publication. To the best of my knowledge, this is the earliest comprehensive and public disclosure of Recursive Intelligence as both a theoretical and operational framework.Core concepts and architectures were finalized and published under CC BY-NC-ND 4.0 on or before March 20, 2025.

Zenodo (CERN European Organization for Nuclear Research)
University of Houston (US), New York University (US)
Openalex Percentile: Top 42%
Obesity, Physical Activity, Diet
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