Excursus: Agent-based modelling and synthetic populations
Teachers: Sarah Wolf, Andreas Geiges — Global Climate Forum
To understand possible transitions of complex systems (like e.g.societies, markets, systems of socio-technical co-evolution) pure data analysis might not be sufficient because such transitions often imply substantial shifts that can hardly be described by pure statistical data extrapolation. Therefore, modelling activities can be a useful complement to data analysis.
This workshop introduces an agent-based model, which is based on synthetic populations, for the global challenge of how to make mobility more sustainable. It illustrates the methodological approach of agent-based modelling, discusses how the process of model development can be accompanied with stakeholder dialogues, explores the interaction between such an agent-based model and the relevant data science tools, and provides some hands-on exercises.
Duration: 2 days.
Prerequisites: basic knowledge of Python
#datascience #complexsystems #agentbased #mobility #sustainability