EF Multi-Agent Systems seeks to build a comprehensive analytical framework to explain macroscopic phenomena arising from the interactions of multiple social agents, including phase transitions, tipping points, and stable pattern formation. This research emphasizes non-standard scenarios not yet systematically treated by mathematical models, with applications spanning the humanities, social sciences, sustainability studies, and biology. Key research directions include developing specialized mathematical models to address agency, trust, and collective action, and creating efficient simulation and control methods for complex social systems, focusing on error control, reduction techniques, and data-enhanced modeling.
Previous denomination: Multi-Agent Social Systems (EF45)
This Emerging Field resulted from joining the former Emerging Fields EF4 and EF5. Successfully completed projects from the two former EFs can be found here:
Emerging Field 4: Particles and Agents
Emerging Field 5: Concept of Change in Historial Processes
Scientists in Charge: Natasa Djurdjevac Conrad, Nicolas Perkowski, Sarah Wolf
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- EF45-2: Effective Stochastic Simulation of Adaptive AB models
Max von Kleist - EF-MA-Sys-1: Emergent Structures in Multi-Component Systems for Embryogenesis
Katharina Hopf, Matthias Liero, Markus Mittnenzweig - EF-MA-Sys-2: Information Flow & Emergent Behavior in Complex Networks
Benedikt Jahnel, Lukas Lüchtrath
- EF45-2: Effective Stochastic Simulation of Adaptive AB models
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- EF4-5: An Agent-Based Understanding of Green Growth
Sarah Wolf - EF4-7: The Impact of Dormancy on the Evolutionary, Ecological and Pathogenic Properties of Microbial Populations
Jochen Blath (until 03/22), Maite Wilke Berenguer - EF4-8: Concentration Effects and Collective Variables in Agent-Based Systems
Jobst Heitzig, Péter Koltai, Nora Molkenthin, Stefanie Winkelmann - EF4-10: Coherent Movements in Co-evolving Agent–Message Systems
Felix Höfling, Robert I.A. Patterson - EF4-12: Agent-Based Models of SARS-CoV2 Transmission: Multilevel Identification and Network-Based Reduction
Nataša Djurdjevac Conrad, Martin Weiser, Sarah Wolf, Edda Klipp
- EF4-13: Modeling Infection Spreading and Counter-Measures in a Pandemic Situation Using Coupled Models
Tim Conrad, Kai Nagel, Christof Schütte - EF5-6: Evolution Models for Historical Networks
Benjamin Ducke, Max Klimm, Guillaume Sagnol - EF45-1: Informing Opinion Dynamics Models with Online Social Network Data
Nataša Djurdjevac Conrad, Ana Djurdjevac, Christof Schütte, Carsten Hartmann, Philipp Lorenz-Spreen - EF45-3: Data Transmission in Dynamical Random Networks
Benedikt Jahnel - EF45-4: Hybrid Models for Large Scale Infection Spread Simulations
Tim Conrad, Kai Nagel, Christof Schütte
- EF45-5: A New Approach to Metastability in Multi-Agent Systems
Maximilian Engel
- EF4-5: An Agent-Based Understanding of Green Growth
Young researchers’ colloquium (EF4 and EF5): CHANGES+ CHange AgeNts: Governing Earth and Society+