Researchers have developed a function that would enable robots to more effectively benefit from deep learning, by deploying a reset that would effectively undo a previous action. The researchers at the University of Washington in Seattle and Microsoft Research describe their work today in Nature. This process would therefore teach robots never to perform an action that is irreversible, for example, driving an automated vehicle over a cliff's edge.
Researchers have developed a function that would enable robots to more effectively benefit from deep learning, by deploying a reset that would effectively undo a previous action. The research, which was published in a recent arXiv paper, outlines how the robot is given a “forward” and “reset” policy that work together; whereby the forward policy learns a skill, whilst hitting the reset forces the robot to learn how it can “leave no trace” of its action. This process would therefore teach robots never to perform an action that is irreversible, for example, driving an automated vehicle over a cliff's edge.