Paper XVII — AI Integration and Stability in Recursive TGRM Networks: Toward Cognitive Reparodynamics
Year: 2025
Type: article
Abstract: This paper extends Paper XVI by introducing AI-integrated recursive TGRM systems operating under cognitive noise (0.01) and adaptive synchronization (1.0) across 40,000 generations. Results demonstrate sustained equilibrium under artificial cognitive coupling, with variance = 0.11, coherence = 0.97, and stability = 0.98. Control systems decayed by generation 100, while TGRM networks maintained zero-latency repair and steady rebound accumulation (~24.6). These results confirm that cognitive-layer coupling preserves reparodynamic stability, marking the first integration of intelligent feedback loops into recursive repair systems. Next phase: Quantum coupling — testing decoherence limits and entanglement-based equilibrium within living Reparodynamics systems.
Author: Jenkins, Cody Ryan
Language: English
Topic: Complex Systems and Dynamics
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7094941764
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