Michael Laver has published a short introduction to agent-based models (ABM) for the social sciences. The Cambridge “Fundamentals” series on Quantitative and Computational Methods for the Social Sciences promises to become quite a resource.
While we still don’t have that many texts on ABM in the social sciences, in my view this is an absolute gem. It’s absolutely hands-on from the beginning, using a stock model (Schelling) in NetLogo. Schelling’s model is often cited because it makes apparent that macro outcomes may result from quite different micro-behaviour/intentions. I guess anyone who’s heard of ABM has also heard of Schelling’s model, which makes it quite useful to illustrate many aspects of modelling. In contrast to other texts, this book uses only a single model throughout the book, but we’re exploring this model in some detail… a level of depth we don’t find in other introductory texts, despite the short length of the book.
In fact, in just 130 pages, we get a clear idea not only of the value and potential of ABM, but also the limitations and drawbacks. With the focus on a single model, the author avoids an uncritical “best of” list, and demonstrates how difficult ABM are: the assumptions we include in the model when we program it are put to the test. In this book, it’s not just an abstract discussion, but we get to see — and (hopefully) understand — that design choices like the size of the neighbourhood in the ABM can greatly influence the result we get. In this sense, I really liked how the book introduces the BehaviorSpace of NetLogo very early: ABM are not just little toys, but can be tools to better understand social life. The last section discusses the ever-present trade-off between understanding and predicting, the trade-off between simplicity and ‘realism’.
I’m not sure whether this was intended, but the book seems quite suitable as a introductory course over a semester, or to help self-learners. In either case, I’d supplement it with Gilbert & Troitzsch to better situate ABM within the social sciences more generally, and Railsback & Grimm where programming ABM takes a more central place, not just modifying code to understand the nature of ABM.
Gilbert, N., and K. Troitzsch. 2005. Simulation for the Social Scientist. Maidenhead: Open University Press.
Laver, Michael. 2020. Agent-Based Models of Social Life: Fundamentals. Cambridge University Press. https://doi.org/10.1017/9781108854665.
Railsback, Steven F., and Volker Grimm. 2019. Agent-Based and Individual-Based Modeling: A Practical Introduction. 2nd ed. Princeton: Princeton University Press.
