Math explains history: Simulation accurately captures the evolution of ancient complex societies. Could it also explain media as culture, whether it's geek culture or history as communication? But does math and history collide? Intense warfare is the evolutionary driver of large complex societies, according to a new mathematical model whose findings accurately match those of the historical record in the ancient world. Geography matters. Just as various geneticists use algorithms to test DNA and find the geographic origins of peoples, mathematicians interested in evolution and history use mathematical simulations to match history to complex cultures.
The question of how human societies evolve from small groups to the huge, anonymous and complex societies of today has been answered mathematically, accurately matching the historical record on the emergence of complex states in the ancient world, explains the new study, "War, space, and the evolution of Old World complex societies," published September 24, 2013 in the Proceedings of the National Academy of Sciences. Authors are Turchin P, Currie T, Turner E, Gavrilets S. 2013. War, space, and the evolution of Old World complex societies. Check out the journal PNAS.
Intense warfare is the evolutionary driver of large complex societies, according to new research from a trans-disciplinary team at the University of Connecticut, the University of Exeter in England, and the National Institute for Mathematical and Biological Synthesis (NIMBioS). The study appears this week as an open-access article in the journal Proceedings of the National Academy of Sciences.
The study's cultural evolutionary model predicts where and when the largest-scale complex societies arose in human history
Simulated within a realistic landscape of the Afro-Eurasian landmass during 1,500 BCE to 1,500 CE, the mathematical model was tested against the historical record. During the time period, horse-related military innovations, such as chariots and cavalry, dominated warfare within Afro-Eurasia. Geography also mattered, as nomads living in the Eurasian Steppe influenced nearby agrarian societies, thereby spreading intense forms of offensive warfare out from the steppe belt.
The study focuses on the interaction of ecology and geography as well as the spread of military innovations and predicts that selection for ultra-social institutions that allow for cooperation in huge groups of genetically unrelated individuals and large-scale complex states, is greater where warfare is more intense.
Quantitative predictions tested empirically
While existing theories on why there is so much variation in the ability of different human populations to construct viable states are usually formulated verbally, by contrast, the authors' work leads to sharply defined quantitative predictions, which can be tested empirically. The model-predicted spread of large-scale societies was very similar to the observed one; the model was able to explain two-thirds of the variation in determining the rise of large-scale societies.
"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. Explaining historical events helps us better understand the present, and ultimately may help us predict the future," explains the study's co-author Sergey Gavrilets, National Institute for Mathematical and Biological Synthesis (NIMBioS) director for scientific activities, in the September 23, 2013 news release, "Math explains history: Simulation accurately captures the evolution of ancient complex societies."
The National Institute for Mathematical and Biological Synthesis (NIMBioS) brings together researchers from around the world to collaborate across disciplinary boundaries to investigate solutions to basic and applied problems in the life sciences. NIMBioS is sponsored by the National Science Foundation, the U.S. Department of Homeland Security, and the U.S. Department of Agriculture with additional support from The University of Tennessee, Knoxville.