Swarm-Intelligence

This paper explores a way for drones to communicate with each other visually, instead of relying on radio, by copying signalling ideas from animals like bees, deer, and peacocks.

Anyone remember smart dust? A cloud of sensors were thrown from a plane into a .. real cloud to study storms, wind patterns, etc.

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.

This paper describes an improved ant-inspired algorithm for finding good paths, such as routes for robots or navigation systems. Instead of searching too randomly, it puts more attention on promising areas early, strengthens better routes as it learns, and discourages unnecessary turns, so it finds smoother and better paths faster.

This paper describes a new way for groups of robots to make a shared choice, based on how ants seem to decide on the best new nest.

This paper looks at how robot swarms can move more smoothly by not only reacting to what nearby robots are doing now, but also by briefly predicting where they are about to move next.

8-10 June 2026 in sunny Germany. ANTS solicits contributions dealing with any aspect of swarm intelligence. Typical, but not exclusive, topics of interest are:

Do emotions and varying environmental stimuli affect the swarms choice of location for the hive? https://arxiv.org/abs/2603.09963

Here are 13 peer-reviewed publications on the infrastructure to make embodied intelligence possible. In order you will find: 1. Human–robot object handover This review surveys how robots pass objects to people and receive them back, framing handover as a foundational capability for human–robot collaboration.

From commercial HVAC to coordinated “swarm intelligence” Encycle is an energy-technology company with origins in Toronto, developing software that helps buildings use less energy and respond more flexibly to the power grid.

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.