"A Canonical Theory of Origins and Development of Social Complexity"
The puzzle of origins of government and social complexity in human and social dynamics -- arguably a characteristic feature of the emergence and long-term evolution of hierarchy and power in the history of civilizations -- has been an enduring topic that has challenged political scientists, anthropological archaeologists, and other social scientists and historians. This paper presents a new computational theory for the emergence of social complexity that accounts for the earliest formation of systems of government (pristine polities) in prehistory and early antiquity. The theory is based on a “fast process” of crisis and opportunistic decision-making through collective action. This core iterative process is “canonical”, in the sense of undergoing variations on a recurring theme of problem-solving, adaptation and occasional failure. When a group is successful in managing or overcoming serious situational changes (endogenous or exogenous to the group, social or physical) a probabilistic phase transition may occur, under a well-specified set of conditions, yielding a long-term (”slow”) process of emergent political complexity and development. A reverse process may account for decay. Formally, the canonical theory is being implemented through the ”PoliGen” agent-based model (ABM), based on the new Multi-Agent Simulator of Networks and Neighborhoods (MASON). MASON is a Java-based simulation environment (akin to Swarm or RePast) developed by George Mason University’s Evolutionary Computation Lab in collaboration with the Center for Social Complexity (CSC). Empirically, the theory is testable with the datasets on polities developed by the Long-Range Analysis of War (LORANOW) Project. This paper focuses on the theoretical concepts, social mechanisms, and basic formal structure underlying the simulation model.