| Autor: |
Helfmann, Luzie, Conrad, Natasa Djurdjevac, Djurdjevac, Ana, Winkelmann, Stefanie, Schütte, Christof |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Commun. Appl. Math. Comput. Sci. 16 (2021) 1-32 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.2140/camcos.2021.16.1 |
| Popis: |
Many real-world processes can naturally be modeled as systems of interacting agents. However, the long-term simulation of such agent-based models is often intractable when the system becomes too large. In this paper, starting from a stochastic spatio-temporal agent-based model (ABM), we present a reduced model in terms of stochastic PDEs that describes the evolution of agent number densities for large populations. We discuss the algorithmic details of both approaches; regarding the SPDE model, we apply Finite Element discretization in space which not only ensures efficient simulation but also serves as a regularization of the SPDE. Illustrative examples for the spreading of an innovation among agents are given and used for comparing ABM and SPDE models. |
| Databáze: |
arXiv |
| Externí odkaz: |
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