Cognitive ARC-AGI-3 solver: 6 human-like drives, 10 reasoning modes (incl. simulation physique), 20 domaines physiques, micro-NN experts (580 params), multi-agent architecture.

Zero-hidden neural networks that solve non-linear problems through temporal depth, not spatial layers. 90.14% MNIST with 480 parameters. Intelligence is not depth — it's resonance. Time is the ultimate hidden layer. OdyssNet proves it.

This project investigates how visual feedback influences throwing accuracy in virtual reality (VR), aiming to understand and enhance the transfer of VR training to real-world skills.