This field is no longer active. It was merged with Concepts of Change in Historical Processes (EF5) to form Multi-Agent Social Systems (EF45) in 2022. All ongoing research projects can be found there.
This Emerging Field focused on modeling and analysis of spatial complex systems involving a large number of small, interacting entities that have a smaller or larger scope of possibilities to take influence on the system. In physics, these entities are often just particles and show little more features than their location in space and one additional property like a mass. Also in physics, but more in the social sciences, there are also a lot of situations in which these entities are much more structured and have highly involved possibilities, they might even be models for human beings that can experience their neighborhood and make their own decisions, in which case we call them agents.
The main focus in EF4 was on developing and analyzing models in situations that had not yet been consistently modeled by mathematics. A “non-mainstream” modeling was intended. Often the biggest difficulty was to take into account the “human factor” in a convincing manner such that mathematical tools could be applied to a rigorous analysis, e.g., of agent-based models and simulations.
The ultimate goal is the detection of macroscopic phenomena like phase transitions, transitions between metastable regimes, and tipping, that emerge from microscopic rules.
Scientists in Charge were Christian Bayer, Wolfgang König, Nicolas Perkowski
Successfully completed projects:
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- EF4-1: Influence of Mobility on Connectivity
Benedikt Jahnel, Wolfgang König - EF4-2: Understanding Tipping and Other Dynamical Transitions in Systems Containing Human Agents
Jobst Heitzig, Péter Koltai, Jürgen Kurths, Christof Schütte - EF4-3: Learning Reduced Models for Large-Scale Mobility ABMs
Carlo Jaeger, Stefan Klus, Christof Schütte, Sarah Wolf - EF4-4: Diffusion in Dynamically Crowded Cells: Stochastic Models from Spatiotemporal Motion Data
Felix Höfling, Carsten Hartmann - EF4-6: Optimal Control of Stochastic Modifed Equations for the Efficient Parametrisation of Deep Neural Networks
Tobias Breiten, Carsten Hartmann - EF4-9*: Multilevel Methods for Agent-Based Epidemic Policy Design
Nataša Djurdjevac Conrad, Max von Kleist, Martin Weiser, Sarah Wolf - EF4-11*: Development of Coarse-Grain Approaches for Geospatially Referenced Agent-Based Models
Edda Klipp
- EF4-1: Influence of Mobility on Connectivity
Projects marked with an asterisk (*) are short-term one-year pilot projects.