Mathematical Model Predicts Evolution of Complex Societies
Intense warfare is the single greatest driver behind the evolution of complex societies, according to a new mathematical model designed to predict the emergence of sophisticated civilizations from small groups.
Published in the journal Proceedings of the National Academy of Sciences, the simulation focuses on the interaction of ecology, geography and the spread of military technology in developing a quantitative look at history.
Current theories regarding the wide range of human ability to establish viable states are largely established verbally; in contrast, the new model puts the societal phenomenon in quantitative terms that can be tested empirically, according to its creators.
In order to evaluate the accuracy of the simulation, the study's authors used it to play out the drama that occurred in the Afro-Eurasian landmass between 1,500 BC and AD 1,500.
During this period, horse-related military innovations dominated regional warfare, including advances in chariots and cavalry. Geography, too, influenced societal expansion as nomads living in the Eurasian Steppe interacted with nearby agrarian communities, resulting in the spread of intense forms of offensive warfare.
In the end, the model's predictions regarding the spread of large-scale societies closely resembled the region's history, explaining 65 percent of the variance in the data.
According to Sergey Gavrilets, director for scientific activities at the National Institute for Mathematical and Biological Synthesis (NIMBioS), the study marks a significant step in framing history as the result of scientifically described processes rather than a series of anecdotes.
"What's so exciting about this area of research is that instead of just telling stories or describing what occurred, we can now explain general historical patterns with quantitative accuracy," he said in a statement, adding that the ability to do so "helps us better understand the present, and ultimately may help us predict the future."
Researchers from the University of Connecticut and the University of Exeter in England also contributed to the study.