The pole that learns not to fall

The most classic reinforcement learning problem: a pole balancing on a cart. A tiny network learns by trying, with the physics and the gradient written by hand. At first it drops instantly; a few hundred episodes later, it holds. Sometimes it stalls — the copy tells you why that is part of the lesson too.