Abstract Lihoreau

Pollinators, such as bees, exploit patchily distributed food resources that replenish over time. Finding an efficient route to visit multiple flowers and return to the nest is a complex optimisation task analogous to the well-known Traveling Salesman Problem in graph theory. Here I will present experiments on bumblebees foraging in meadows of computer-controlled flowers equipped with automated tracking systems to discuss how foragers locate flowers and often develop near-optimal circuits to link them as they gain experience. Comparative analyses of our behavioural data across experimental conditions reveal simple search patterns and learning heuristics that bees, and virtually all nectar foraging animals, may use to efficiently exploit their complex foraging environments with brains of limited computational power.