Complex machinery, from drones to surgical robots, sometimes behaves like a wild mustang: full of disorder and whims, where the slightest touch triggers a storm. Instead of rote memorization of formulas, the new method observes the system like a horse breaker. A mathematical trick (the Koopman operator) draws on the ideas of David Hilbert and translates chaotic prancing into a calm dance, much like spacetime curvature in Einstein's theory makes orbits simple. Thus a standard model of behavior is born, which the algorithm refines like a rider polishing a steed's reflexes.

Then the breaking in begins: a virtual jockey calculates every move, keeping the system on the right rein. Even with fragmentary data, as if blindfolded, the algorithm chooses near-perfect actions. Mathematical guarantees, like sturdy reins, prevent mistakes.

A test on the 'stubborn pendulum'—the Duffing oscillator, whose behavior resembles the expansion of the universe (a calm before a leap)—showed that the virtual controller tames its chaos. They say the same equations describe the heartbeat, so the algorithm may one day assist cardiologists. The technology will soon teach drones to hover in hurricanes and factory robots to juggle loads.