Researchers at the University of California, Berkeley, have developed algorithms that enable robots to learn motor tasks through trial and error using a process that more closely approximates the way humans learn, marking a major milestone in the field of artificial intelligence.
They demonstrated their technique, a type of reinforcement learning, by having a robot complete various tasks -- putting a clothes hanger on a rack, assembling a toy plane, screwing a cap on a water bottle, and more -- without pre-programmed details about its surroundings.