Dear @Imre, just for the case that you have not met this publication that is related to the issue which you have raised. It is very good question. Please, explain your image in terms of terms that you have used. What is regular system? What is difference between complicated and complex system...? 

Predictability, Complexity, and Learning !

There are connections between the predictive information and measures of complexity that have been dened both in learning theory and the analysis of physical systems through statistical mechanics and dynamical systems theory...

 Dear Ljubomir,

Thank you very much indeed for calling my attention to this  paper. I briefly looked at it, and seems to be interesting. With regards to the terminology, let me offer the included figure. This explains our categorization of systems (actually, this is a landscape from the perspective of CPSs). A complicated system by definition is a system that has a very large number of consituents (components), a large number of mutual relationships among the consituents, a large number of dynamic relationships with the environment, as well as strongly context- and time-dependent behaviour, and for these reasons it is challenging and difficult to model, analyse, simulate, design, and control it. These systems are composable, and with restrictions, reductionist. Complex systems in addition show various forms of emergence due to their holistic behaviour. These system are compositional and non-reductionist. Exactly these things were motivating my question.

Thanks dear @Imre. System's science and control is my major! So we do have different types of adaptive systems in complex systems according to the last figure, right? Where would the term "large-scale-systems" would fit?

Ljubomir, excellent. Then you can advise me on the correctnes of these propositions. I am dealing with cognitive engineering of smart (second-generation) cyber-physical systems. We are also very much interested in international cooperation. Kind regards, Imre