"The shape of their network relieves some of the cognitive load for the ants; they don't need to think about it," Simon Garnier, a biologist at the New Jersey Institute of Technology, told NBC News. "The shape of their networks has constrained their movement in a way that is more efficient for them."
The findings have implications for understanding ant biology as well as how humans design transportation networks for the flow of people, information and goods.
Garnier and colleagues have spent several years pursuing questions about the movement of ants around the environment — how they establish complicated networks that efficiently link their nests with food, for example.
The scientific literature well documents that ants use chemical markers called pheromones to line their trails. Less clear is what goes on inside an ant's brain when it reaches an uneven fork in a built network. Does it spend a lot of time measuring angles and weighing options? Or does it just go with the flow?
The question gave the researchers a good excuse to put to work some ant-like robots they'd been building.
"We programmed our robots so that they would not actively measure the angle of the (fork in the road), they would just move and carry on," Garnier explained. And they were programmed to carry on, so to speak, in the same general direction.
Real ants carry on in this manner, which is called "exploratory behavior," in order to prevent them from running in circles around their nests, establishing a well-traveled, pheromone-laced path that leads nowhere.
The robots, called Alice, laid their own version of pheromones in the form of light, thanks to a system of cameras and projectors coordinated to illuminate the wake of each robot's path. In addition, each robot is equipped with two light sensors that mimic ant antennae so that they can follow established trails.
The experiment showed the robots, like ants, rather quickly find and establish the quickest route through a maze from point A to point B with the aid of the pheromone-like light trails, and that they can do so without weighing options when they reach a fork on the road.
Instead, ants appear programmed, like the robots, to take the easiest path — the one with the lowest deviation from straight ahead — without thinking about it. The combination of pheromones and networks with asymmetrical forks, the research suggests, allows ants to navigate efficiently without mentally taxing decision-making.
We humans do a similar thing when walking down a crowded street, noted Garnier. "You're just going to go wherever there is an open space, but you're not going to take into account all of the individuals one by one and everything that is around you," he said.
For people, this automated decision-making allows the brain to focus on other issues, such as the road not taken, as did the poet Robert Frost when he penned the famous lines, "Two roads diverged in a wood, and I, / I took the one less traveled by, / And that has made all the difference."
The findings are reported online Thursday in the journal PLoS Computational Biology.