Emergent Behaviour

Researchers found that adding small random movements (“wiggling”) to robots in dense swarms prevents congestion and improves throughput. The approach mirrors biological systems where stochastic motion helps ants, cells, and animals avoid deadlock in crowded environments.

A German startup has moved biohybrid swarm systems from concept to field-tested deployment, using living insects equipped with neural interfaces, sensors, and secure communications to operate as coordinated reconnaissance swarms.

Georgia Tech researchers developed swarms of simple robotic particles that coordinate and self-organize without electronics, software, or sensing, relying entirely on physical design and local interactions.

By encoding interaction rules directly into physical structure, researchers showed that coordinated group behavior can emerge without digital control, sensors, or centralized systems.

This article says animals in groups, like bees, fish, or birds, can solve problems together through many small local interactions, and engineers are using those same ideas to build robot swarms that can act without a central controller.

adaptive-emergent now has a more focussed direction. Part one of this series looked at the history from 2015 to 2021; Part two explained why adappt.

At adaptive-emergent, we are looking for simple behaviours in nature that add up to quite complex ones. The resulting model can be used to massively scale basic business rules into a whole that is more than the sum of its parts.