Five Lines Of Code Could Change The Way We Think About AI - AI Summary

Each robot "is very greedy and wants to do what they want to do." If they all work together, both robots can achieve their goal, but they can't communicate with the other robots in any meaningful way. But the AMOLF team wants to get away from that -- they wanted to stay as simple as possible, Overvelde says, in order to make the behaviors simple as well, because, "the more complex the behavior, it's hard to tell in the end what it's going to do." Abstract: One of the main challenges in robotics is the development of systems that can adapt to their environment and achieve autonomous behavior. By letting each unit adapt its behavior independently using a basic Monte Carlo scheme, the assembled system is able to learn and maintain optimal behavior in a dynamic environment as long as its memory is representative of the current environment, even when incurring damage. As a result, such a distributed learning approach can be easily scaled to larger assemblies, blurring the boundaries between materials and robots, paving the way for a new class of modular "robotic matter" that can autonomously learn to thrive in dynamic or unfamiliar situations, for example, encountered by soft robots or self-assembled (micro)robots in various environments spanning from the medical realm to space explorations.