et al. [@cully_robots_2015] nicely points out that a hierarchical organization and structuring of the behavioral space helps in finding solutions for complex motor control problems. But, on the other hand, we think that the idea of a static, stationary representation might be too restricting, to address the whole range of behavioral adaptivity. It appears that the footfall pattern emerges as a form of an observable behavioral code, but it seems questionable as a substrate for control. So, while such a lower-dimensional space appears helpful to make dynamic problems (ranging from small changes in the environment towards large, constantly changing environments) accessible, we would argue that a static given representation appears too narrow and too much tuned towards a specific kind of behavior. Instead, we would like to suggest to consider a slightly different take on such a behavioral space which does not treat the behavioral space as a specific type of representation, but rather as an observation of invariances that stem from the underlying systems. In six-legged walking such an approach has shown to be very promising with respect to adaptivity. Our Walknet approach consists of six decentralized control structures, one for each leg which makes decisions on which action 