Cyber-Physical Systems (CPS) consist of tightly integrated and coordinated computational and physical elements. They focus on interaction with highly uncertain environment with the limited resources. By introducing IoT and Industry 4.0, the CPSs are connected to each other to meet the emerging more complex requirements. These interconnected CPSs constitute complex systems called Cyber-physical System of Systems (CPSoS) in which there may be emergent behaviour, lack of central control, dynamic structure, and need for autonomy. Therefore, CPSoS cannot be designed and managed using theories and tools from only one single domain.
A key point in a CPSoS is to obtain knowledge out of the information, collected by monitoring the environment. This knowledge can improve the control and feedback mechanism. This capability leads to the next generation of CPSoS with timely and more accurate decisions and actions called Smart CPSoS (sCPSoS). These smart systems can analyze a situation and make decisions based on the available data in an adaptive manner, to perform smart actions. However, such intelligent techniques put yet additional complexity to the systems, specifically to the computational part.
Thus, these systems of the future have a high complexity (both from structural and behavioural points of view) throughout their lifecycle, including modeling & simulation, design & implementation, validation & verification, deployment, execution & monitoring, and maintenance & evolution. There is a need for new methodologies, architectures, process models, and frameworks to tackle this complexity.
To overcome the challenges in the development and operation of sCPSoS, modeling techniques can be used for different aspect and various levels of abstraction in the system. To this end, appropriate modeling paradigms should be chosen for each aspect/level. These models and modeling paradigms will be integrated, hence called multi-paradigm modeling (MPM), to represent the whole system. Specifically, the idea is to integrate agent paradigm with the model-based system engineering (MBSE) for both modelling & simulation phase as well as execution and monitoring phase in the lifecycle of sCPSoS. Agent based system engineering (ABSE) uses software intelligent agents to successfully cross-fertilize the fields of systems engineering and artificial intelligence. In this way, the autonomy, dynamic behaviour and smart-ness of sCPSoS can be handled by intelligent agents, integrated with MBSE models.