This paper describes the use of System Dynamics models to manage the very substantial risks associated with complex design, development and production projects. The authors present a systematic approach to controlling the risks associated with a project’s cost, schedule and technical performance.
Researchers for complex systems become more and more important in modern science. System dynamics has done its significant work for the integration of System Theory and Computer Science in this field. Each dynamic system forms a complex causality network. Now we can use the panweighted network in Pansystems Theory for the dynamic system modeling, and further perform the automatic reasoning on this model. This new ideal may be developed into a deep seated issue in AI. In this article, the method of both modeling and automatic reasoning on a panweighted network in dynamic systems will be introducted together with a simple and typical example in System dynamics. The further extention of this new method will be discussed in other articles.
“Commons-type” computer simulations are increasingly popular tools for helping students grasp the underlying trap of individual versus collective rational action in situations of joint ownership and finite resources. Historically, these simulations have been designed on mainframe or mini computers with site limited capacity for either visual or auditory feedback. This paper presents a preliminary commons-type game designed for use with the emerging local extended-area MacIntosh based networks. This paper also tests whether providing diagrammatic and verbal descriptions of the inherent resource and behavioral feedbacks enables players to avoid the fundamental commons trap: Short-term individually rational actions which result in collectively irrational consequences.
This paper focuses on the financial markets crash of October 1987 to examine the effects of trading strategies and other institutional structures on price behavior during this period. It presents a system dynamics model which looks at average, aggregate stock prices. It specifies connections among various trading sites and techniques. In particular, it examines the influence of financial and technological innovations such as stock-index futures and other derivative instruments and high speed order execution and transaction systems on market performance. A major conclusion is that the financial markets are characterized by complex structures only partially economic in nature. This suggests that the interplay between market pricing behavior and institutional behavioral reactions are more complex than is currently believed.
Central Europe faces a decade of restructuring due to the move from centrally planned economies to free markets. Its economic evolution into the current structure of resource utilization and output composition is traced by using a dynamic model. Major production factors and their interaction are simulated to quantify the issues of the transition: these include the transformation of traditional industries and their reorientation towards services, the parallel transfer of ownership of assets and financial intermediaries, restructuring the labor pool, demographic changes and energy efficiency.