from EAs that has proposed how such a structure might look like. While this allows to cover a range of interesting behavioral problems, we will argue that it still falls short with respect to adaptive behavior and the problem space that animals deal with. The example is taken from six-legged robot walking which is a complex task as it involves a high number of degrees of freedom (at least three per leg and at least 18 overall). Still, even simple animals (with respect to brain size) are capable of very adaptive and unparalleled behavior, climbing through trees, uneven terrain, dealing with leg loss etc. [@schilling_walknet_2013]. When turning towards motor control approaches, the space of possible behaviors is typically too large for an exhaustive search. A hierarchical approach could help through introducing suitable stepping stones and search for partial solutions to these. This directly leads to the question on what kind of representation a higher level could operate and which would provide a substrate for novelty based search. Cully et al. [@cully_robots_2015] demonstrated in a fascinating study how for the example of a six-legged robot (and another example of a robot arm) a suitable problem space representation can be found. The 