The New York Times, November 12, 2007
If you have ever observed ants marching in and out of a nest, you might have been reminded of a highway buzzing with traffic. To Iain Couzin, such a comparison is a cruel insult – to the ants.
Americans spend a total of 3.7 billion hours a year in congested traffic. But you will never see ants stuck in gridlock.
Army ants, which Dr. Couzin has spent much time observing in Panama, are particularly good at moving in swarms. If they have to travel over a depression in the ground, they erect bridges so that they can proceed as quickly as possible.
“They build the bridges with their living bodies,” said Dr. Couzin, a mathematical biologist at Princeton University and the University of Oxford. “They build them up if they’re required, and they dissolve if they’re not being used.”
The reason may be that the ants have had a lot more time to adapt to living in big groups. “We haven’t evolved in the societies we currently live in,” Dr. Couzin said.
By studying army ants – as well as birds, fish, locusts and other swarming animals – Dr. Couzin and his colleagues are starting to discover simple rules that allow swarms to work so well. Those rules allow thousands of relatively simple animals to form a collective brain able to make decisions and move as if they were a single organism.
Deciphering those rules is a big challenge, however, because the behavior of swarms emerges unpredictably from the actions of thousands or millions of individuals.
“No matter how much you look at an individual army ant,” Dr. Couzin said, “you will never get a sense that when you put 1.5 million of them together, they form these bridges and columns. You just cannot know that.”
To get a sense of swarms, Dr. Couzin builds virtual models as computer programs. Each model contains thousands of individual agents, which he can program to follow a few simple rules. To decide what those rules ought to be, he and his colleagues head out to jungles, deserts or oceans to observe animals in action.
In the case of army ants, Dr. Couzin was intrigued by their highways. Army ants returning to their nest with food travel in a dense column. This incoming lane is flanked by two lanes of outgoing traffic. A three-lane highway of army ants can stretch for as far as 450 feet, or 140 meters, from the ant nest, comprising hundreds of thousands of insects.
What Dr. Couzin wanted to know was why army ants do not move to and from their colony in a mad, disorganized scramble. To find out, he built a computer model based on some basic ant biology. Each simulated ant laid down a chemical marker that attracted other ants while the marker was still fresh. Each ant could also sweep the air with its antennas; if it made contact with another ant, it turned away and slowed down to avoid a collision.
Dr. Couzin analyzed how the ants behaved when he tweaked their behavior. If the ants turned away too quickly from oncoming insects, they lost the scent of their trail. If they did not turn fast enough, they ground to a halt and forced ants behind them to slow down. Dr. Couzin found that a narrow range of behavior allowed ants to move as a group as quickly as possible.
It turned out that these optimal ants also spontaneously formed highways. If the ants going in one direction happened to become dense, their chemical trails attracted more ants headed the same way. This feedback caused the ants to form a single packed column. The ants going the other direction turned away from the oncoming traffic and formed flanking lanes.
To test this model, Dr. Couzin and Nigel Franks, an ant expert at the University of Bristol in England, filmed a trail of army ants in Panama. Back in England, they went through the film frame by frame, analyzing the movements of 226 ants.
Eventually they found that the real ants were moving in the way that Dr. Couzin had predicted would allow the entire swarm to go as fast as possible. They also found that the ants behaved differently if they were leaving the nest or heading back. When two ants encountered each other, the outgoing ant turned away further than the incoming one. As a result, the ants headed to the nest end up clustered in a central lane, while the outgoing ants form two outer lanes.
Dr. Couzin has been extending his model for ants to other animals that move in giant crowds, like fish and birds. And instead of tracking individual animals himself, he has developed programs to let computers do the work.
To study humans, Dr. Couzin teamed up with researchers at the University of Leeds. They recruited eight people at a time to play a game. Players stood in the middle of a circle, and along the edge of the circle were 16 cards, each labeled with a number. The scientists handed each person a slip of paper and instructed the players to follow the instructions printed on it while not saying anything to the others. Those rules correspond to the ones in Dr. Couzin’s models. And just as in his models, each person had no idea what the others had been instructed to do.
In one version of the experiment, each person was instructed simply to stay with the group. As Dr. Couzin’s model predicted, they tended to circle around in a doughnut-shaped flock. In another version, one person was instructed to head for a particular card at the edge of the circle without leaving the group. The players quickly formed little swarms with their leader at the head, moving together to the target.
The scientists then sowed discord by telling two or more people to move to opposite sides of the circle. The other people had to try to stay with the group even as leaders tried to pull it apart.
As Dr. Couzin’s model predicted, the human swarm made a quick, unconscious decision about which way to go. People tended to follow the largest group of leaders, even if it contained only one additional person.
Dr. Couzin and his colleagues describe the results of these experiments in a paper to be published in the journal Animal Behavior.
Copyright 2007 The New York Times Company. Reprinted with permission.