To figure out the best way for a robot to move, designers have turned to snakes,cheetahs, fish and even mermaids for inspiration. But to figure out the best way for a robot to learn, they’re going to the dogs.
A team led by computer scientists at Washington State University’s Intelligent Robot Learning Laboratory set up a robot training program that builds in the kinds of fits and starts that a dog might employ when it’s learning a task from its human master. When the virtual robot is unsure what to do, it slows down and looks for feedback. But once it’s figured out the task, it runs through the job lickety-split.
The “Strategy-Aware Bayesian Learning” model, which was laid out in Singapore last week at the International Conference on Autonomous Agents and Multi-agent Systems, was developed in anticipation of an age when regular folks rather than programmers would have to teach robots what to do.
“We want everyone to be able to program, but that’s probably not going to happen,” WSU Professor Matthew Taylor said today in a news release. “So we needed to provide a way for everyone to train robots – without programming.”