Formalising Agent Reasoning—The Paso Doble of Data and Theory

One of the core assumptions made when building agent-based simulation models is how the agents decide or reason about the action to take next. The mode of reasoning is usually the same for all agents and over time within the simulation run. However, is this adequate? There exist several frameworks that describe multi-mode reasoning, however how do we know what we need? To engage with this core question, we reflect on this modelling process, by using CAFCA—one of these multi-mode frameworks—and reflect on the reasoning dimension in a social dilemma decision situation. More specifically, using existing qualitative inquiry on group dynamics in a common pool resource dilemma—not designed to elicit different types of reasoning—we introduce our hunt for reasoning hints and reflect on what insights/data we would need to make an informed decision about the reasoning(s) in our modelling and how to obtain this.