Curling robot beats top-ranked human teams in major breakthrough

Sign up to our free weekly IndyTech newsletter delivered straight to your inbox Sign up to our free IndyTech newsletter Sign up to our free IndyTech newsletter SIGN UP I would like to be emailed about offers, events and updates from The Independent. The Curly robot, developed by a joint German-South Korean research team, used deep reinforcement learning to learn the best way to slide stones along the ice and land on the target. Curly makes use of two robots – a “Thrower-Curly” and a “Skip-Curly” – in order to both assess the target area and to slide the stone towards it. The only difference to matches at professional competitions was the lack of sweepers – the players who brush the ice ahead of the stone as it slides in order to influence its speed and trajectory The researchers from Korea University and the Berlin Institute of technology trained the robots AI on a computer game that simulates the physical properties of the stones and the ice. “Our proposed adaptation framework extends standard deep reinforcement learning using temporal features, which learn to compensate for the uncertainties and nonstationarities that are an unavoidable part of curling.” The research was published in the journal Science Robotics on Wednesday.