Antastic

Leaving breadcrumbs (well, pheronome trails) to lead the way. https://pmc.ncbi.nlm.nih.gov/articles/PMC10956014/

This article reports on a robot system inspired by how ants communicate using pheromone trails. Instead of real chemicals, the robots follow artificial “pheromone” signals so they can coordinate with one another and make group decisions in a similar way to ants.

Fractals! Ant colonies, materials like gases and liquids, and robot swarms may all follow a similar underlying pattern: lots of individuals behaving somewhat randomly, but still producing large-scale collective behaviour.

The algorithm models ant nest-selection behaviour to solve the “best-of-n” consensus problem using only local signalling. It demonstrates how response thresholds, recruitment, and biasing mechanisms enable robust distributed agreement without central control.

This study shows ants make faster pheromone-guided decisions in low-distraction environments, suggesting that signal clarity vs. environmental noise is a critical factor in stigmergic coordination.

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.

https://www.science.org/content/article/ants-best-humans-test-collective-intelligence