The course focuses on the substantive problems, theories, and related computational models in a number of core areas of policy modelling (e.g., research policy, public policy). The methodological challenge in policy modelling is bridging the gap between policy practice and the scientific realm of formal models. Participants learn to master these challenges by applying complexity sensitive computational methods—with a particular focus on agent-based modelling (ABM)—using the Netlogo software and Python. For the full course description, a detailed syllabus, and registration click here.
