Regenerative Intelligence via Reparodynamics: Five Domain Integration with Predictive Repair and Coherence Memory

This paper presents experimental evidence for regenerative intelligence arising within a five-domain Reparodynamics stack integrating digital, biological, quantum, environmental, and information-entropic systems. Controlled perturbations up to 85% intensity revealed unprecedented self-repair behavior — including rapid recovery (0.08 s), yield rebounds exceeding 12%, and stability overshoots of +7% above baseline. At peak load, the system achieved sustained infinite equilibrium with no collapse, suggesting a measurable transition from resilience to regeneration. The findings introduce quantitative metrics such as Repair Yield per Energy (RYE) and Coherence Memory, enabling replication, cross-lab validation, and open scientific critique. All data, prompts, and response transcripts are released under open-science principles for independent verification.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-05
DOI
https://doi.org/10.5281/zenodo.17532878
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
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article

Regenerative Intelligence via Reparodynamics: Five Domain Integration with Predictive Repair and Coherence Memory

Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
article

Regenerative Intelligence via Reparodynamics: Five Domain Integration with Predictive Repair and Coherence Memory

article en

Abstract

This paper presents experimental evidence for regenerative intelligence arising within a five-domain Reparodynamics stack integrating digital, biological, quantum, environmental, and information-entropic systems. Controlled perturbations up to 85% intensity revealed unprecedented self-repair behavior — including rapid recovery (0.08 s), yield rebounds exceeding 12%, and stability overshoots of +7% above baseline. At peak load, the system achieved sustained infinite equilibrium with no collapse, suggesting a measurable transition from resilience to regeneration. The findings introduce quantitative metrics such as Repair Yield per Energy (RYE) and Coherence Memory, enabling replication, cross-lab validation, and open scientific critique. All data, prompts, and response transcripts are released under open-science principles for independent verification.

Zenodo (CERN European Organization for Nuclear Research)
Czech Academy of Sciences, Institute of Hydrology (CZ), Dynamic Research (United States) (US)
Openalex Percentile: Top 23%
Neural Networks and Reservoir Computing
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