Extending quantum theory with AI-assisted deterministic game theory
A new AI framework treats quantum experiments as a game to predict individual outcomes, challenging 'free choice' assumptions.
Deep Dive
Researchers Florian Pauschitz, Ben Moseley, and Ghislain Fourny developed an AI-assisted framework that interprets quantum experiments as deterministic games. Using neural networks to learn reward functions containing hidden variables, they applied it to the EPR 2-2-2 experiment. This acts as a proof-of-concept for a local-realist hidden-variable model, offering a new avenue to extend quantum theory by replacing traditional 'free choice' with a 'contingent free choice' assumption.
Why It Matters
This could provide a deterministic, local explanation for quantum phenomena, a foundational goal in physics.