Cross-Domain Transfer Learning in Developmental Knowledge Graphs Without Training

We present Vyan, a developmental AI agent that achieves 29–70% cross-domain transfer learning across four domain pairs without any gradient-based training, pre-trained embeddings, or large language model reasoning. The agent builds knowledge through a dual-graph neural architecture separating emotional from analytical cognition, and transfers knowledge via graph-structural embeddings and multi-head attention-driven activation dynamics. The agent also demonstrates metacognitive self-awareness, including the ability to say "I don't know" when evidence is insufficient.