In this chapter Steve Phelan discusses the uniqueness of complexity theory, in which researchers seek the simple rules that underlie complex systems. This approach is at the heart of the use of agent-based models of human systems.
People sometimes wonder how complexity theory differs from other endeavors, such as systems theory or traditional science. I believe that the answer lies in considering how each approach treats cause and effect. In traditional science we tend to assume that simple causes lead to simple effects. Take Newton’s well-known formula that force equals the product of mass and acceleration (F=MA) or Einstein’s famed relationship between energy and mass, E MC2. In both of these cases, relatively simple relationships hold between the variables.
In the 1950s and 1960s, systems theory introduced the notion that phenomena that appear to have simple causes, such as unemployment, in fact have a variety of complex causes: complex in the sense that the causes are interrelated, nonlinear, and difficult to determine. Systems theorists adopted a holistic approach, which, in its most radical form, argued that everything is complex, that everything affects everything else, and that any given phenomenon, such as unemployment, cannot be studied without looking at the entire context in which it is embedded.