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A spatial-temporal model of early complex polities is described in which cycles of consolidation and collapse emerged during simulations. Self-organized criticality (SOC) also was clearly observed. SOC is characteristic of simulations for iterative physical phenomena such as earthquakes and forest fires. Social scientists are interested in SOC as a theoretical framework to understand cyclical human cultural processes. In particular there has been considerable speculation that SOC underlies polity cycling. The current model is an attempt to move beyond speculation by demonstrating that: 1) the model unequivocally exhibits SOC, 2) there is a self-evident correspondence between the model's structure and actual polities as indicated in the archaeological record, 3)hierarchical settlement patterns emerge during simulations, and 4) simulated population distributions are consistent with empirical rank-size survey data typical of early complex polities.

Insights into prehistoric region-wide political consolidation were suggested by simulation results from an agent-based model of pre-state societies. The case study was the late prehistoric period circa 2500 BC to AD 1000 in the Lake Titicaca basin of Peru and Bolivia. Over a series of simulation runs the model produced a range of alternative political pre-histories. A substantial proportion of those runs were classified as matching the scenario archeologists believe actually happened during this time period. Classification was based on multidimensional quantitative measures of empirical criteria for the emergence of simulated macro-level patterns corresponding to observed patterns in the archaeological record. The model's structure consisted of a grid of cells, each scaled to 1.5 km x 1.5 km, representing the geography, hydrology, and agricultural potential of the 50,000 sq. km basin. A collection of multiple agents--Settlements, Peoples, Polities, and Chiefs (political leaders) -- interacted with the environmental grid and with each other. The agents' behavior was modeled as micro-level condition-action rules based on the hypothesized causal factors of: agriculture, migration, competition, and trade. Internal structure and dynamics as well as the simulation results showed strong indicators of the model's structural realism. Uncertainties associated with the model were also assessed.