Our Lines of Research
Our research focuses on the structure and dynamics of complex social and economic systems, comprised of a large number of interacting agents.
Our methodological approach can be best described as data-driven modeling. I.e. we analyze big data to detect statistical regularities in such systems. We build large-scale agent based models to simulate the interaction dynamics on the "micro" level, to obtain the system's dynamics on the "macro" level. We further use rigorous mathematical models to understand such systems. We have achieved our goal if the agent-based model, after being calibrated against real data, produces a macro dynamics that not only resembles, but matches the observed dynamics at the system's level.
Such a level of understanding, although hard to achieve, allows us to target the problem of systems design, as we see it: what mechanisms do we have to change on the agent's level, to obtain a more desirable outcome on the system's level: more reliability, more cooperation, better dissemination of information, faster adaptivity of a system to exogeneous and endogeneous changes.
The broad range of research questions we address can be loosely grouped into the following areas, each of which is described on a separate page with links to our relevant publications.
Fundamental Concepts of Complex Systems
Adaptive Social Organizations
Structure and Dynamics of Economic Networks