Physicists at the University of California, Irvine, have developed an artificial intelligence system that can autonomously design theoretical physics models, a task traditionally carried out by human theorists. The approach allows researchers to explore large, uncharted areas of particle physics theory, helping identify promising new explanations for the behavior of neutrinos.

The system is called Autonomous Model Builder (AMBer), and was developed by a research team led by UC Irvine doctoral candidates Victoria Knapp-Pérez and Jake Rudolph in the Department of Physics and Astronomy. The work is published in Communications Physics.

AMBer uses reinforcement learning, a form of artificial intelligence that learns through trial and error rather than by following predefined instructions. As it explores possible particle physics theories, the system evaluates its own choices and improves over time.