It almost looks like a wounded animal.
There’s that little hop in its gait, the way it looks tentative as it springs forward from its haunches, the not-exactly-straight trajectory of its path. Except this isn’t an injured animal. It is a robot. And even with two broken legs, this hexapod can figure out how to keep going.
Which means that what looks like a slightly sad (if persistent) hunk of metal making its way across a hard floor represents something much bigger, actually. New research published on Wednesday in Nature finds that machines can change their behavior to adapt to being broken—they can learn and iterate based on self-reflection. In other words, they can act like animals.
“Animals understand the space of possible behaviors and their value from previous experience,” the researchers Antoine Cully, Jeff Clune, Danesh Tarapore, and Jean-Baptiste Mouret wrote in Nature. “The key insight here is that robots could do the same.”
The authors of the study refer to their work as an “intelligent trial-and-error algorithm,” and they emphasize how different it is from earlier research in the realm of what’s known as reinforced learning. The way it works: A robot realizes it isn’t moving the way it ought to, so it tests alternative ways of getting where it needs to go based on an extensive database of movements. “The robot does not know exactly that it is broken,” the researchers wrote in a statement about their work. “It only knows that its performance has suddenly dropped. It has no internal sensors to detect whether any of its components are damaged.” (The lack of sensors is key because it means building these systems would be much cheaper, they say.)