Each test consisted of 500 generations of eight robots. To mimic what might happen in nature, the successful robots from each generation were "randomly assorted and subjected to crossovers and mutations…forming the next generation," the researchers explained. And although the 33 "genes" were randomly distributed at first, "the robots' performance rapidly increased over the 500 generations of selection," the researchers noted. And along with acuity at collecting the food, "the level of altruism also rapidly changed over generations," with those robots around more closely "related" individuals becoming the most altruistic.Not only is altruism am inevitable consequence of evolution, we can even quantify it using very simple genetic and evolutionary systems.
Aside from demonstrating Hamilton's rule in a quantifiable—if artificial—system, the work also shows that "kin selection does not require specific genes devoted to encode altruism or sophisticated cognitive abilities, as the neuronal network of our robots comprised only 33 neurons," the researchers noted in their paper.
We have two parameters - population size (8) and number of generations till termination (500). I'd be interested to see the mutation rate, crossover rate, and parental selection mechanisms though, to determine whether it is a truly genetic or a degenerate evolutionary algorithm at the end.
And I'd be really interested in using a meta-genetic algorithm to optimise those parameters.