Abstract

There is a long history of applying theories from various disciplines to archaeological research. This dissertation builds on that tradition and aims to illustrate the utility of applying a self-organizing systems theory perspective to ancient human societies. The theory of self-organization was developed in physics and has been applied successfully to biological systems, especially concerning the interactions of social insects. In human groups, self-organizing systems theory can be used to understand how some traditions and practices within a culture may be implemented, changed, and maintained without direct leadership. Self-organization is the emergence of new forms, trends or behaviors, which are influenced by interactions between agents, their communities and their built and natural environments. There are three distinguishing components of a self-organizing system: emergence, local interaction (neighbor-neighbor interaction and stigmergy), and scale of analysis. Self-organization may be present at various scales, or units, of human action and can be seen by transformations or consistencies in the material record, which are proxies for the change or maintenance of traditions and practices.

Three archaeological case studies are the core of this analysis: Megalithic South India of the first millennium B.C., Cahokia and the Middle Mississippi River Valley of the second millennium A.D., and Iron Age and Roman Britain of the first millennium A.D. These examples were chosen because they represent three levels of human social organization: simple, intermediate, and complex. I examine these three case studies to first determine how self-organization arises in groups of various socio-political complexity and then to understand the specific impact those non-directed behaviors have on their development. In this dissertation, I identify the nature of human interactions, understand how local practices can generate large-scale societal changes, and determine the role of self-organization in the creation of sociopolitical complexity.