Why do so many public and private organizations suffer from recurrent crises? Why do so many policies fail? Why do some organizations thrive while others fail? Why is it difficult to identify the possible consequences of the implementation of new policies?
The human experience is characterized by multiple sets of interconnected decision processes that create high levels of complexity and generate dynamics that often are counterintuitive and difficult to manage. Such difficulty dramatically increases under conditions of uncertainty, stress, and high consequence, as in the case of complex systems for threat and response management. In complex systems, designing and regulating decision processes to improve performance is difficult because of the pervasiveness of time delays and nonlinear responses that cause system behavior. This course introduces basic principles underlying dynamic feedback systems and presents a set of concepts and tools for thinking through complex system-wide problems that challenge the ability to design, operate, and manage complexity in multi organizational and intergovernmental policies and programs. Students will learn to understand complex interactions using dynamic modeling and simulation and will learn to diagnose and solve complex system-level problems by applying systems science approaches. Students will learn the basic principles underlying growth, exponential decay, and sigmoid growth in dynamic feedback systems. The principles will be explored by building and analyzing computer models of social systems with examples drawn from economic, urban, security, energy, and biological systems.
The course is intended both for those who wish to understand policy studies conducted by others employing computer simulation, and for those who want to become simulation modelers. It provides the conceptual and technical knowledge necessary to conceptualize complex dynamic policy problems, formulate appropriate simulation models, and use models for policy analysis.