| Abstract: |
Social evolutionary theory seeks to explain increases in the scale and
complexity of human societies, from origins to present. Over the course of the
twentieth century, social evolutionary theory largely fell out of favor as a
way of investigating human history, just as advances in complex systems
science and computer science saw the emergence of powerful new conceptions of
complex systems, and in particular new methods of measuring complexity. We
propose that these advances in our understanding of complex systems and
computer science should be brought to bear on our investigations into human
history. To that end, we present a new framework for modeling how human
societies co-evolve with their biotic environments, recognizing that both a
society and its environment are computers. This leads us to model the dynamics
of each of those two systems using the same, new kind of computational
machine, which we define here. For simplicity, we construe a society as a set
of interacting occupations and technologies. Similarly, under such a model, a
biotic environment is a set of interacting distinct ecological and climatic
processes. This provides novel ways to characterize social complexity, which
we hope will cast new light on the archaeological and historical records. Our
framework also provides a natural way to formalize both the energetic
(thermodynamic) costs required by a society as it runs, and the ways it can
extract thermodynamic resources from the environment in order to pay for those
costs -- and perhaps to grow with any left-over resources. |