A robot equipped with artificial intelligence (AI) can excel at the Olympic sport of curling — and even beat top-level human teams.
Players in a curling match slide stones across an ice rink towards targets. Success requires precision and strategy, but the game is less complex than other real-world applications of robotics. That makes curling a useful test case for AI technologies, which often perform well in simulations but falter in real-world scenarios with changing conditions.
Using a method called adaptive deep reinforcement learning, Seong-Whan Lee and his colleagues at Korea University in Seoul created an algorithm that learns through trial and error to adjust a robot’s throws to account for changing conditions, such as the ice surface and the positions of stones.
The team’s robot, nicknamed Curly, needed a few test throws to calibrate itself to the curling rink where it was to compete. But once acclimated, the robot won three out of four matches against elite human competitors. The algorithm reduced Curly’s throwing error — the mean distance from the target’s centre — to about one-third of that of a non-adapting robot.