Rise and Fall of Rome Can Be Modeled

January 24, 2011 

Researchers claim they can mathematically model the major processes that cause states and empires to emerge, survive, and collapse at the scale of decades to centuries. 

Sergey Gavrilets, David Anderson, and Peter Turchin created a spatially explicit, agent-based model of the emergence of early, complex societies via warfare. So called polities are represented as hierarchically structured networks of villages whose size, power, and complexity change as a result of conquest, secession, internal reorganization (via promotion and linearization), and resource dynamics. 

A key prediction of the model is continuous stochastic cycling in which the growth of individual polities in size, wealth/power, and complexity suddenly collapses. The model's dynamics, they noted, are mainly controlled by two parameters: one scales the relative advantage of wealthier polities in between and within-polity conflicts; the other is a leader's expected time in power.

The results suggest that the stability of complex societies hinges on outcomes of conflicts; on wealth and power; on well-defined and accepted means of succession; and on internal control mechanisms. 

"In the last several decades, mathematical models have been traditionally important in the physical, life, and economic sciences, but now they are also becoming important for explaining historical data," said Gavrilets. "Our model provides theoretical support for the view that cultural, demographic, and ecological conditions can predict the emergence and dynamics of complex societies." 

The researchers' findings, summarized in the article, "Cycling in the Complexity of Early Societies," appeared in the premier issue of Cliodynamics: The Journal of Theoretical and Mathematical History (2010). 

Source: NIMBioS (January 20, 2011)