Simulating Imperial Dynamics and Conflict in the Ancient World

The development of models to capture large-scale dynamics in human history is one of the core contributions of the cliodynamics field. Crucially and most often, these models are assessed by their predictive capability on some macro-scale and aggregated measure, compared to manually curated historical data. We consider the model predicting large-scale complex societies from Turchin et al. (2013), where the evaluation is done on the prediction of "imperial density": the relative frequency with which a geographical area belonged to large-scale polities over a certain time window. We implement the model and release both code and data for reproducibility. Furthermore, we assess its behaviour against three historical data sets: the relative size of simulated polities vs historical ones; the spatial correlation of simulated imperial density with historical population density; the spatial correlation of simulated conflict vs historical conflict. At the global level, we show good agreement with the population density (R2<0.75), and some agreement with historical conflict in Europe (R2<0.42, a lower result possibly due to historical data bias). Despite being overall good at capturing these important effects, the model currently fails to reproduce the shapes of individual imperial polities. Nonetheless, we discuss a way forward by matching the probabilistic imperial strength from simulations to inferred networked communities from real settlement data.