"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. (...) 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). (...) "Even simple mass-recruiting ants have much more complex and labile problem solving skills than we ever thought. Contrary to previous belief, the pheromone system of ants does not mean they get stuck in a particular path and can't adapt. Having at least two separate pheromones gives them much more flexibility and helps them to find good solutions in a changing environment. Discovering how ants are able to solve dynamic problems can provide new inspiration for optimisation algorithms, which in turn can lead to better problem-solving software and hence more efficiency for human industries." - Amira from Bookmarklet

See also: Ant Colony Optimisation http://ff.im/qlP1R - Amira

Wow... this was news when I was PhD... like, 8 years ago - Egon Willighagen

well.. nobody said that ACO algorithms are the latest news ;) but Reid & Sumpter's tests using the Towers of Hanoi puzzle under dynamic changes are.. Here is a research article http://www.scribd.com/full... - Amira