Agent-based Models: Because they’re worth it?

We address the question of when the relative complicatedness of spatial agent-based models (ABMs) compared to alternative modelling approaches can be justified. The spectrum of ABM types from simple, abstract models to complicated models aspiring to realism makes a single answer impossible. Therefore we focus on identifying circumstances where the advantages of ABMs outweigh the additional effort involved. We first recall the reasons for building any model: to simplify the phenomena at hand to improve understanding. Thus, the representational detail of ABMs may not always be desirable. We suggest that critical aspects of the phenomena of interest that help us to assess the likely usefulness of ABMs are the nature of the decisions which actors make, and how their decisions relate to the spatio-temporal grain and extent of the system. More specifically, the heterogeneity of the decision-making context of actors, the importance of interaction effects, and the overall size and organization of the system must be considered. We conclude by suggesting that there are good grounds based on our discussion for ABMs to become a widely used approach in understanding many spatial systems.