A brand-new book from Springer press is sure to become a staple in our bookshelves. Agent-based Modeling and Simulation in Archaeology provides a much-needed update, in one solid volume, on the methods and practice of using agent-based modeling to understand the past.
The two introductory chapters serve to highlight the utility of abm, in general terms with Lake’s “Explaining the Past with ABM” chapter, and in more specificity with Swedlund et al’s “Modeling Archaeology” chapter, which delves into the case-study of Artificial Anasazi. Lake specifically tells us that there is a large
“advantage of adding computer simulation to the archaeologists toolkit: not only [does] it force us to codify and make explicit our assumptions, but… it also allows us to explore the outcome of behaviors which can no longer be observed and for which there is no reliable recent historical record. In addition, it allows us to explore the outcome of behavior aggregated at the often coarse grained spatial and temporal resolution of the archaeological record.” (Lake, p. 9, this volume).
So say we all.
The most useful portion of this book to those new to agent-based modeling is probably the Methods section. While Railsback and Grimm have written the seminal text on learning agent-based modeling, their ecological approach can sometimes leave archaeologists scratching their heads. The four chapters on methods in this volume, however, concretely link ABM approaches with archaeology, discussing the unique sets of challenges we face in archaeology and how simulation methods can address those questions. Those concerned with questions that are tied intrinsically to the landscape will especially enjoy Koch’s “Geosimulation” chapter, while each of us should probably memorize Popper and Pichler’s “Reproducibility” chapter, and attempt to keep our work transparent, as they so rightly suggest.
The Applications section of this book provides four unique case studies that use ABM in varied situations. Each of these is well-researched and provide different viewpoints in how to use ABM effectively in archaeology. From Crema’s analysis of fission-fusion dynamics, to Kowarik et al’s and Danielisová et al’s chapters on prehistoric economies, to Barceló et al’s look at territoriality and social networks, these chapters are sure to provide good fodder for learning about different archaeological systems and how ABM can bring light to muddy portions of our understanding.
Despite being heavily cited, this book left out (as authors) a few pioneers in agent-based modeling in archaeology (Kohler, Premo), which may be a reflection of the mostly-European-based authorship of the chapters in this book, or is likely due to the fact that this book is based on a meeting held in Vienna. If the book has an updated version it would be good to include other voices from across the pond.
The heavy price tag of the book ($175 on Amazon, currently $120 on Springer) might make this beyond the scope for students to whom this book seems aimed. Hopefully a less costly paperback version, or e-reader version, of this book will come out to increase its accessibility.
All in all, this book will be a worthwhile addition to our bookshelves, and I can already imagine incorporating it into courses in agent-based modeling.