Researchers in Switzerland have developed an experimental system that allows them to track the evolution of social cues. The experiments do not, however, involve the Swiss population. Instead, the individuals involved are small-wheeled robots that compete for food and emit light to signal to their neighbors. Evolution occurs because their behavior is controlled by a set of 33 digital "genes." In a paper that will be released later this week by PNAS, the authors describe how these robots evolve to avoid tipping their competitors off to the site of a food source.
These robots and the ecosystem they "live" in is described in a paper they have published previously in Current Biology. The robots themselves have a floor sensor, wheels, a camera, and light that can display different colors. They're set loose in an arena that contains two hubs, one with food that improves their health, and a second with poison that damages it. The hubs look identical from a distance, and can only be distinguished at close range using the floor sensor.
The authors can turn finding food into a competition, as only eight robots can be in direct contact with the hub at once. By putting 10 robots into the arena, the authors can register the health of the competitors at the end, and allow the healthiest to "reproduce." In robot terms, this acts just like sexual reproduction; the 33 genes are mutated, recombined, and randomly assorted, and the results fed into the next generation of robots. Because conditions are so well defined, the robots are actually somewhat superfluous, as the entire system can be modeled by computers, and the authors can determine the precise behaviors of the winners and losers of each generation.
There's a movie of the robots in action derived from the earlier publication, in which the robots are programmed to turn blue once feeding, and their peers have evolved to zoom in on the blue light.
In that situation, the blue is a necessary consequence of feeding, and so it provides a social cue to a robot's peers, who are also its evolutionary competitors. In the new publication, the authors experiment with social cues that are far more subtle.
To start with, they ran an experiment where the robots emitted blue light at random, which disassociates the behavior from feeding. However, since the robots sit still once they start feeding, even random blue flickers produced a relative abundance of blue light near the food. So, starting from a population that was neutral towards blue light, by generation nine, the robots had evolved so that they were attracted to light, a behavior that wound up predominating in future generations.
The authors then switched to a system where both the attraction to blue lights and the frequency with which a robot activates it were under genetic control. Not surprisingly, the emission of all light quickly plunged, but it never vanished entirely; once it dropped below a certain level, there wasn't enough information content for it to be selected against. As a result, the frequency with which the robots turned blue elsewhere in the arena slowly began to rise again, although lighting up when near food stayed low.
Similarly, the attraction towards blue light never entirely vanished. However, because some robots evolved to emit light whenever they weren't near food, the robots attracted to blue light were joined by a number that were repelled by it. As a result, although the population was, on average, slightly attracted to blue light, there were always some individuals closer to the extremes, either very attracted to it, or repulsed by it.
The authors appear to suggest that this model may provide a way to understand some of the social signals that we see in other species, many of which seem baffling to a human equipped with only common sense. In these experiments, the robots demonstrated how something that was inadvertent—random flashes of blue light—could become a life-or-death social cue, and lead to the evolution of strategic behavior for both the signal and the robot's response to it.