The Modeling Process

Abstract

Considerable interest currently exists in the application of the systems approach to the solution of societal, political, and environmental problems. The essence of this systems approach is modeling, the capability to describe large-scale complicated interactive systems by symbolic representations so that inferences regarding the effects of alternative system configurations can be easily and rapidly structured. The modeling process is itself becoming better understood as a direct extension of the scientific method. Furthermore, the applicability of statistical methodology to the design and analysis of experiments with computerized symbolic models is leading to wider acceptance of these representations as tools of considerably credible scientific stature. This paper presents a taxonomy of 24 model categories and, in a discussion of the scientific method and the modeling process, indicates the evaluations pertinent to the selection of a modeling medium appropriate to particular systems studies. The dynamic stochastic simulation model is shown to be the most general category of symbolic models which are amenable to facile organized experimentation. The application of such models to the understanding and solution of societal, political, psychological, medical, judicial, environmental, social, economic, and biological problems is indicated and is considered imminently practicable.