Neurodevelopment as blueprint: biological validation of the dual-architecture AGI framework.
- 1Independent Researcher, Chengdu, Sichuan, China.
Abstract
Human intelligence does not develop linearly: it follows a precise phase sequence. This article presents the hypothesis that this neurodevelopmental timeline corresponds to the dual-architecture artificial general intelligence (AGI) system previously proposed by the author, covering the 10 architectural components. We hypothesize that AGI development may be constrained by similar phase sequencing, address key objections (see Sections 3.1, 5.4, 5.5, and 5.6 for explicit objection-response pairs) through formal arguments, and provide indirect supporting evidence for six individual mechanisms on the MuJoCo platform: four-method anti-forgetting comparison: elastic weight consolidation (EWC), synaptic intelligence (SI), memory-aware synapses (MAS), and Naive. Curiosity-driven exploration, training stability analysis, multimodal cross-prediction, and warm-start routing analysis reveal negative transfer in genuinely novel scenarios, and a multi-novelty gradient experiment spanning five gravity levels (1.0×-2.0×) identifies a crossover threshold at approximately 1.25×-1.50× gravity on HalfCheetah-v5. An appendix provides a formal mathematical theory of token migration with two formal sketches and one implication.
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BibTeX
@article{chen2026neurodevelopment,
title = {{Neurodevelopment as blueprint: biological validation of the dual-architecture AGI framework.}},
author = {Nan Chen},
journal = {Frontiers in robotics and AI},
year = {2026},
month = oct,
doi = {10.3389/frobt.2026.1902952},
url = {https://europepmc.org/article/MED/42923129},
note = {CC BY},
}
RIS
TY - JOUR
TI - Neurodevelopment as blueprint: biological validation of the dual-architecture AGI framework.
AU - Nan Chen
PY - 2026
DA - 2026/10/08
JO - Frontiers in robotics and AI
DO - 10.3389/frobt.2026.1902952
UR - https://europepmc.org/article/MED/42923129
AB - Human intelligence does not develop linearly: it follows a precise phase sequence. This article presents the hypothesis that this neurodevelopmental timeline corresponds to the dual-architecture artificial general intelligence (AGI) system previously proposed by the author, covering the 10 architectural components. We hypothesize that AGI development may be constrained by similar phase sequencing, address key objections (see Sections 3.1, 5.4, 5.5, and 5.6 for explicit objection-response pairs) through formal arguments, and provide indirect supporting evidence for six individual mechanisms on the MuJoCo platform: four-method anti-forgetting comparison: elastic weight consolidation (EWC), synaptic intelligence (SI), memory-aware synapses (MAS), and Naive. Curiosity-driven exploration, training stability analysis, multimodal cross-prediction, and warm-start routing analysis reveal negative transfer in genuinely novel scenarios, and a multi-novelty gradient experiment spanning five gravity levels (1.0×-2.0×) identifies a crossover threshold at approximately 1.25×-1.50× gravity on HalfCheetah-v5. An appendix provides a formal mathematical theory of token migration with two formal sketches and one implication.
SN - 2296-9144
ER -