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|CSDMS meeting institute co1=Helmholtz Centre for Environmental Research – UFZ, Leipzig
|CSDMS meeting institute co1=Helmholtz Centre for Environmental Research – UFZ, Leipzig
|CSDMS meeting country co1=Germany
|CSDMS meeting country co1=Germany
|CSDMS meeting email address co1=volker.grimm@ufz..de
|CSDMS meeting email address co1=volker.grimm@ufz.de
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{{Presenters presentation
{{Presenters presentation

Revision as of 14:27, 7 January 2025

CSDMS 2025: Exploring Earth's Surface with Models, Data & AI


Pattern-oriented agent-based modeling to achieve structural realism and testable predictions



Steve Railsback

Lang Railsback & Associates, United States
steve@langrailsback.com
Volker Grimm Helmholtz Centre for Environmental Research – UFZ, Leipzig Germany


Abstract
Both too simple and too complex models have limited payoff in understanding real systems and making reliable inferences. Pattern-oriented modeling (POM) is a strategy to find the right intermediate level of complexity. It is based on the goal of making a model simultaneously reproduce multiple patterns that have been observed at different scales and levels of organization. The patterns are used as multiple criteria for model design, selection, and parameterization. POM was developed for agent-based models, but can be used for any model type. We will introduce POM using examples and conceptual exercises, and participants will conduct an exercise, using a NetLogo model we provide, to test how well alternative versions of a key submodel cause the model to reproduce observed patterns. Participants should bring a computer with NetLogo (version 6.0 or later; http://ccl.northwestern.edu/netlogo) and software for graphical and statistical analysis of results (e.g., Excel, R).

Please acknowledge the original contributors when you are using this material. If there are any copyright issues, please let us know (CSDMSweb@colorado.edu) and we will respond as soon as possible.

Of interest for:
  • Terrestrial Working Group
  • Coastal Working Group
  • Marine Working Group
  • Education and Knowledge Transfer (EKT) Working Group
  • Cyberinformatics and Numerics Working Group
  • Hydrology Focus Research Group
  • Chesapeake Focus Research Group
  • Critical Zone Focus Research Group
  • Human Dimensions Focus Research Group
  • Geodynamics Focus Research Group
  • Ecosystem Dynamics Focus Research Group
  • Coastal Vulnerability Initiative
  • Continental Margin Initiative
  • Artificial Intelligence & Machine Learning Initiative
  • Modeling Platform Interoperability Initiative
  • River Network Modeling Initiative