Adaptive agents, intelligence, and emergent human organization: Capturing complexity through agent-based modeling

Perhaps the most difficult challenge in understanding social phenomena is their intractably complex nature. For much of the 20th century social scientists attempted to unravel the complexities of the social realm by emulating the methodologies of the natural sciences. Although these approaches enhanced social science research, they have fallen short of capturing emergent behavior and self-organization.

For some years now, new approaches to the study of complex adaptive systems have offered researchers in both the physical and social sciences an important new theoretical and methodological framework for helping to understand a variety of nonlinear, dynamic systems. Complex adaptive systems are characterized often by “agents” interacting or capable of interacting with each other in dynamic, often nonlinear and surprising ways. Most social phenomena would readily fit the description of a complex adaptive system. The difficulty researchers have faced, given the opaque character of social processes, is to develop methodologies appropriate for better exploring such complex adaptive systems.

A growing number of social scientists, dissatisfied with traditional methodologies, are seeking new methods for exploring the complexities of social dynamics. One of the emerging developments is the use of agent-based modeling and simulation to examine how social phenomena …