The predominant paradigm in cognitive science has been the cognitivistic one, exemplified by the Physical Symbol Systems Hypothesis . The cognitivistic approach generated hopes that one would soon understand human thinking - hopes that up till now have still not been fulfilled. It is well-known that the cognitivistic approach, in spite of some early successes, has turned out to be fraught with problems. Examples are the frame problem, the symbol grounding problem, and the problems of interacting with a real physical world.In order to come to grips with the problems of cognitivism the study of embodied autonomous systems has been proposed, for example by Rodney Brooks. Brooks' robots can get away with no or very little representation. However, this approach has often been criticized because of the limited abilities of the agents. If they are to perform more intelligent tasks they will need to be equipped with representations or cognition - is an often heard argument. We will illustrate that we are well-advised not to introduce representational or cognitive concepts too quickly. As long as we do not understand the basic relationships between simple architectures and behavior, i.e. as long as we do not understand the dynamics of the system-environment interaction, it is premature to spend our time with speculations about potentially useful architectures for so-called high-level processes.This paper has a tutorial and a review aspect. In addition to presenting our own research, we will review some of the pertinent literature in order to make it usable as an introduction to New AI .