Neurodevelopment as blueprint: biological validation of the dual-architecture AGI framework
Year: 2026
Type: article
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.
Source: Frontiers in Robotics and AI
Author: Nan Chen
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W7221040113