An ant colony is the last place you’d expect to find a maths whiz, but University of Sydney researchers have shown that the humble ant is capable of solving difficult mathematical problems.
These findings, published in the Journal of Experimental Biology, deepen our understanding of how even simple animals can overcome complex and dynamic problems in nature, and will help computer scientists develop even better software to solve logistical problems and maximise efficiency in many human industries.
Using a novel technique, Chris Reid and Associate Professor Madeleine Beekman from the School of Biological Sciences, working with Professor David Sumpter of Uppsala University, Sweden, tested whether Argentine ants (Linepithema humile) could solve a dynamic optimisation problem by converting the classic Towers of Hanoi maths puzzle into a maze.
Finding the most efficient path through a busy network is a common challenge faced by delivery drivers, telephone routers and engineers. To solve these optimisation problems using software, computer scientists have often sought inspiration from ant colonies in nature – creating algorithms that simulate the behaviour of ants who find the most efficient routes from their nests to food sources by following each other’s volatile pheromone trails. The most widely used of these ant-inspired algorithms is known as Ant Colony Optimisation (ACO).
