AI: Trial And Error Empowers Reinforced Learning In Robot
Researchers 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.
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.
Conventional, but impractical, approaches to helping a robot make its way through a 3-D world include pre-programming it to handle the vast range…