Swarm Intelligence in Natural and Synthetic Lives

Abstract

Real world phenomena are inherently nonlinear and complex in a way that usually cannot be understood from the first principle. Yet intelligence behaviors appear in biological systems, which are shaped by billions of years of evolution, to solve natural challenges. Here, we show a form of collective intelligence at microbial level, emerged in a swarm of strongly interacting single-cell organisms as they navigate through complicated topologies and avoid dangers in dynamical environments. We then develop a robotic system in which autonomous robots with bio-inspired functions move over a programmable adaptive landscape. The robot swarm can self-organized to optimize resource consumption and survive stressful conditions by emulating organic biology, exhibiting what we call robobiology. We conclude by sketching out future research directions with scientific questions that our robotic system can address.