Modeling Dynamic Systems

Abstract

Model building is central to our understanding of real-world phenomena. We all create mental models of the world around us, dissecting our observations into cause and effect. Such mental models enable us, for example, to successfully cross a busy street. Engineers, biologists, and social scientists simply mimic their observations in a formal way. With the advent of personal computers and graphical programming, we can all create more complex models of the phenomena in the world around us. As Heinz Pagels has noted,² the computer modeling process is to the mind what the telescope and the microscope are to the eye. We can model the macroscopic results of microphenoma, and vice versa. We can simulate the various possible futures of a dynamic process. We can begin to explain and perhaps even to predict.

Indeed, from Pythagoras through pyramidology, extreme irrationalities have often been presented in numerical form. Astrology for centuries used the most sophisticated mathematical treatments available—and is now worked out on computers: though there is, or used to be, an English law which provided that “every person pretending or professing to tell Fortunes, or using any subtle Craft, Means or Device … shall be deemed a Rogue and Vagabond.”¹