Emerging Field 45 “Multi-Agent Social Systems”

This Emerging Field focuses on modeling and analysis of complex social systems. These systems are inherently spatio-temporal in nature, consisting of a large number of interacting agents and their (built or natural) environment. The agents, in turn, have individual degrees of freedom and influence on system states. This gives rise to multi-scale effects in both social and environmental interactions.

The dominant presence of dynamics and the involvement of randomness are of particular relevance, both to the modelling and the analysis (e.g., as uncertainty in data, or by the usage of probability theory).

The over-arching objective is to derive a rigorous understanding, or at least an explanation, of macroscopic phenomena that emerge from microscopic rules, like phase transitions, transitions between meta-stable regimes, tipping, or the emergence of long-term patterns.

A central aim of this undertaking is the description of reactions to change and transformation. This also applies to the effects of co-evolution within a system of interest or among other, connected systems. Closely related to this, key scientific concepts, like coherence, the aforementioned co-evolution, resilience, tipping points, etc. must be cast into mathematical terms, making them operational elements for theoretical analysis.

Examples of social systems considered in this Emerging Field stem from the humanities (historical developments, e.g. as understood from archaeological data), social and sustainability science (humans and socio-economic and environmental dimensions), engineering (humans and their technologies), and biology (interactions between different species, incl. humanity). The main focus, however, is on settings that have not yet been modeled consistently by mathematics (“non-mainstream” modeling). Frequently, one challenge will be to account for the “human factor” in a convincing manner, such that rigorous mathematical principles can be applied, while retaining the flexibility of tools such as agent-based models and simulations. Another challenge is to bridge mathematical modeling and the epistemological paradigms of the application disciplines.


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: Christian Bayer, Natasa Djurdjevac Conrad, Wolfgang König