Systems simulation. The simulation of social system evolution with spiral loops

Abstract

Social system evolution is taken to be the result of the interaction of autonomous social systems for the purposes of this paper. An autonomous social system is understood to be a multilevel decision-making system which basically uses two types of rules in order to maintain its goals: rule-setting (strategies) and rule-fulfilling (policies). This article gives an introduction to a recently developed methodology which makes it possible to represent rule-setting and rule-fulfilling decision-making processes in social systems with their structural and behavioral differences. This new methodology also allows us to simulate evolutionary processes in social systems based on these two forms of decision making. The new methodology combines the continuous feedback loop concept of system dynamics with intelligent logical loops, which we call spiral loops. The spiral loop concept, which is based on new developments in evolutionary theory and in the field of artificial intelligence, is used to represent the rule-setting strategic decisions which generate qualitative changes and evolution. The continuous feedback loop concept is used to model the rule-fulfilling policy decisions of social systems which can generate quantitative changes in interaction processes. The potential of this new approach is demonstrated with two important social system applications: (1) The “portfolio simulation model” which helps us to explain and to design the evolution of multibusiness firms in duopoly markets; and (2) the “know-how transfer model” which explains the evolution of multinational corporations in less developed countries and which helps to improve the simultaneously ongoing process of know-how transfer.