Reparodynamics and Neural Self-Repair: Recursive TGRM Stabilization under Degenerative Drift Conditions
Year: 2025
Type: article
Abstract: This open validation paper documents the fifth recursive TGRM simulation demonstrating Reparodynamics’ capacity to maintain system integrity under degenerative drift conditions. The neural degeneration model tested baseline entropy 0.6 across 200 generations, comparing a decaying control population with a recursive TGRM agent capable of continuous adaptive self-repair. Control integrity collapsed to ≈0 by generation 20. Recursive TGRM stabilized at ≈25.3 post-decay, maintaining 1.00 repair efficiency and cumulative rebound ≈12.0 by generation 120 — signifying sustained equilibrium through recursive correction of neural degradation analogs. These findings extend Reparodynamics into the domain of algorithmic neuro-repair, supporting the feasibility of entropy-bounded resilience models applicable to neurodegeneration research and synthetic brain simulations.
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: W7093340638
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