Paper XVII — AI Integration and Stability in Recursive TGRM Networks: Toward Cognitive Reparodynamics
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.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-24
- DOI
- https://doi.org/10.5281/zenodo.17435189
- Primary Topic
- stochastic dynamics and bifurcation
- Type
- article
- Field-Weighted Citation Impact
- 0.00