This document presents the physiological and cognitive integration layer of the Unified Resonant Cascade Model (URCM), extending its scope from mathematical regularization to embodied adaptive systems.URMC introduces a grounded connection between memory persistence, resonance stability, and the metabolic analogs of artificial cognition.It demonstrates how the same cascade equations governing physical energy transfer can describe neural and informational flows in self-developing AI systems.The framework emphasizes biological coherence, energetic homeostasis, and cognitive resilience as the foundation for continuous AI learning and memory evolution.This is part of the URC Framework series (URCT–URCM–URMC), developed collaboratively by independent researchers exploring the boundary between physics, cognition, and artificial life.
Oleg Zmiievskyi (Sat,) studied this question.
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