Process-Based Modeling and Design of Dynamical Systems

Process-based modeling is an approach to constructing explanatory models of dynamical systems from knowledge and data. The knowledge encodes information about potential processes that explain the relationships between the observed system entities. The resulting process-based models provide both an explanatory overview of the system components and closed-form equations that allow for simulating the system behavior. In this paper, we present three recent improvements of the process-based approach: (i) improving predictive performance of process-based models using ensembles, (ii) extending the scope of process-based models towards handling uncertainty and (iii) addressing the task of automated process-based design.