Building Empirical Multiagent Models from First Principles When Fieldwork Is Difficult or Impossible

Abstract

This Chapter informs the reader about how to create and parameterize empirical multiagent models from first principles when fieldwork is difficult or impossible to conduct and data is primarily of qualitative nature. Empirical multiagent models have become ever more popular over the last decade. While informing models using statistical and geospatial data can orient itself on more established techniques and standards, methodological challenges persist in regards to using qualitative data for informing and parameterizing models. Protocols such as ODD are welcome and helpful devices—and hence used in this Chapter—but qualitative data comes with its own peculiarities. The most important of which is, for modeling purposes, that qualitative data tends to inform the logic of agent behavior. The emphasis I thus put on qualitative data to make model design decisions based on evidence and first principles will be reflected by soft adaptations of the ODD protocol. Arguably this may amount to a deeper insight the Chapter is providing: Whereas the usage of such frameworks as ODD increases model reliability, validity is built using qualitative empirical data for informing and parameterizing the agent and model behavior.