Presenters-0672
From CSDMS
CSDMS 2025: Exploring Earth's Surface with Models, Data & AI
Pattern-oriented agent-based modeling to achieve structural realism and testable predictions
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).
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