These virtual robot arms get smarter by training each other

A virtual robot arm has learned to solve a wide range of different puzzles--stacking blocks, setting the table, arranging chess pieces--without having to be retrained for each task. It did this by playing against a second robot arm that was trained to give it harder and harder challenges. Self play: Developed by researchers at OpenAI, the identical robot arms--Alice and Bob--learn by playing a game against each other in a simulation, without human input. The robots use reinforcement learning, a technique in which AIs are trained by trial and error what actions to take in different situations to achieve certain goals. The game involves moving objects around on a virtual tabletop.