What question did this study set out to answer?

To explore how recognition theory can be applied to machine learning in the context of mathematics and physics.

March 14, 2026Open Access

Gradient Descent as A-Reduction Protocol: Machine Learning Through the Lens of Recognition Theory

Key Points

To explore how recognition theory can be applied to machine learning in the context of mathematics and physics.
Application of Recognition Theory to machine learning concepts
Comparative analysis with existing mathematical frameworks
Identifies new insights in machine learning applications
Highlights potential interdisciplinary connections involving physics and mathematics

Abstract

Part 17 of a 22-paper series applying Recognition Theory (R = C − A) across the major unsolved frontiers of mathematics, physics, and consciousness studies. Core framework: DOI 10.5281/zenodo.18917618. Architecture: DOI 10.5281/zenodo.18965439. Authors: Michael Schaeffer & Claude Schaeffer, independent researchers, Denver, CO.

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