# Data-driven model reduction of agent-based systems using the Koopman generator

@article{Niemann2021DatadrivenMR, title={Data-driven model reduction of agent-based systems using the Koopman generator}, author={Jan-Hendrik Niemann and Stefan Klus and Christof Sch{\"u}tte}, journal={PLoS ONE}, year={2021}, volume={16} }

The dynamical behavior of social systems can be described by agent-based models. Although single agents follow easily explainable rules, complex time-evolving patterns emerge due to their interaction. The simulation and analysis of such agent-based models, however, is often prohibitively time-consuming if the number of agents is large. In this paper, we show how Koopman operator theory can be used to derive reduced models of agent-based systems using only simulation data. Our goal is to learn…

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Identification of Nonlinear Systems Using the Infinitesimal Generator of the Koopman Semigroup—A Numerical Implementation of the Mauroy–Goncalves Method

- Computer ScienceMathematics
- 2021

The subtle numerical details of the Koopman operator-based linearization method are addressed and a new implementation algorithm is proposed that alleviates these problems.

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