Um dos autores responde a esta questão na secção dos comentários:
"That is not correct (I am one of the authors). From our FAQ: The robot is not simply picking a working gait from a small library of options. The map (or library) has over 13,000 behaviors. Yet the robot finds one that works after trying around 8 of them. Clearly, it is not testing them all. It is able to do this because the robot, like a scientist, carefully chooses which experiments to conduct to find an answer as quickly as possible (here, the answer the robot seeks is how to keep functioning despite its damage).The map of behaviors is not hand-designed: it is learned by the robot. The robot uses a computer simulation of itself to create this map ahead of time. These maps can be quite large. In our experiments with the six-legged robot, the map contained over 13,000 gaits. While generating that map is computationally intensive, it only has to be done once per robot design before the robots are deployed. Importantly, this map does not represent all possible behaviors the robot can make. The space of all possible behaviors that is searched to find these 13,000 high-performing behaviors is unimaginably vast. In fact, it contains 10^47 possible behaviors, which is about how many water molecules on the planet Earth! That would be too many for our robot scientist to search through once damaged. Instead, we search through this vast space ahead of time to find 13,000 high-performing gaits (via a new algorithm we invented called "MAP-Elites"). In short, whereas previous algorithms searched for needles in fields of haystacks, we gather the needles ahead of time, so we are searching through a pile of needles to find the right one."