Communication among robots, and bacteria
Laurent Keller at the University of Lausanne did some work on communication. The research involved robots and neural networks. From Discover:
Each robot had a pair of wheeled tracks, a 360-degree light-sensing camera, and an infrared sensor underneath. The robots were controlled by a program with a neural network architecture. In neural networks, inputs come in through various channels and get combined in various combinations, and the combinations then produce outgoing signals. In the case of the Swiss robots, the inputs were the signals from the camera and the infrared sensor, and the output was the control of the tracks.
The scientists then put the robots in a little arena with two glowing red disks. One disk they called the food source. The other was the poison source. The only difference between them was that food source sat on top of a gray piece of paper, and the poison source sat on top of black paper. A robot could tell the difference between the two only once it was close enough to a source to use its infrared sensor to see the paper color.
Each robot wears a kind of belt that can glow, casting a blue light. The scientists now plugged the blue light into the robot circuitry. Its neural network could switch the light on and off, and it could detect blue light from other robots and change course accordingly. The scientists started the experiments all over again, with randomly wired robots that were either related or unrelated, and experienced selection as individuals or as colonies.
At first the robots just flashed their lights at random. But over time things changed. In the trials with relatives undergoing colony selection, twelve out of the twenty lines began to turn on the blue light when they reached the food. The light attracted the other robots, bringing them quickly to the food. The other eight lines evolved the opposite strategy. They turned blue when they hit the poison, and the other robots responded to the light by heading away.
As to bacteria
The results were impressive, although perhaps not surprising to people who are familiar with experimental evolution with bacteria. From their randomly wired networks, the robots evolved within a few dozens generations until they were scoring about 160 points a trial. That held in all twenty lines. Each program consists of 240 bits, which means that it could take any of 2 to the 240th power configurations. Out of that unimaginable range of possibilities, the robots in each line found a fast solution.
From Popular Science
The experiment involved 1,000 robots divided into 10 different groups. Each robot had a sensor, a blue light, and its own 264-bit binary code "genome" that governed how it reacted to different stimuli. The first generation robots were programmed to turn the light on when they found the good resource, helping the other robots in the group find it.
The robots got higher marks for finding and sitting on the good resource, and negative points for hanging around the poisoned resource. The 200 highest-scoring genomes were then randomly "mated" and mutated to produce a new generation of programming. Within nine generations, the robots became excellent at finding the positive resource, and communicating with each other to direct other robots to the good resource.
However, there was a catch. A limited amount of access to the good resource meant that not every robot could benefit when it was found, and overcrowding could drive away the robot that originally found it.
After 500 generations, 60 percent of the robots had evolved to keep their light off when they found the good resource, hogging it all for themselves. Even more telling, a third of the robots evolved to actually look for the liars by developing an aversion to the light; the exact opposite of their original programming!