Ants Do Math: How Insect Colonies Intelligently Optimize Their Searches for Food

You wouldn't think that tiny insects could be capable of complex problem-solving; but that's the case with ants. Scientists have taken a closer look at these insects' movements and have found out that while they appear random at first, together they are organized in an orderly way that allows them to search out an area more efficiently.

"Ants have a nest so they need something like a strategy to bring home the found they find," said Lixiang Li, one of the researchers, in a news release. "We argue that this is a factor, largely underestimated so far, that actually determines their behavior."

In order to better understand ant foraging behavior, the scientists essentially put everything they knew about it into equations and algorithms. They then fed this data into computers. Overall, they assumed that there are three stages of the complex feed-search movements of a colony. First, scout ants circle in a chaotic way before becoming tired and going back to the nest to rest; when one of them finds a piece of food, they take a tiny piece back to the nest and leave a trail of pheromones to lead others back to the food. Other ants will follow the trail and bring more food home; yet because the trail is initially so weak, the ants will follow different trails. Over time, though, the trail will be optimized as more ants use the best trail and leave pheromones to mark it.

"While the single ant is certainly not smart, the collective acts in a way that I'm tempted to call intelligent," said Jurgen Kurths, one of the researchers, in a news release. "The principle of self-organization is known from for instance fish swarms, but it is the homing which makes the ants so interesting."

The findings reveal a little bit more about ant foraging behavior, but they also reveal a bit more about the fundamental patterns of nonlinear phenomena. In fact, the mathematical model that the scientists created to describe the ant behavior is applicable to very different kinds of animals and provides a new perspective on behavioral patterns of humans in areas that are as diverse as the evolution of web services.

The findings are published in the journal Proceedings of the National Academy of Sciences.