Systems Science

Systems science is defined by the Systems Science and Mathematics Department here at Washington University as an approach which views an entire system of components as an entity rather than simply an assembly of individual parts; each component is designed to fit properly with the other components rather than to function by itself. It is a recent field of development, having its origins in new mathematical thinking developed during the fifties and sixties. It is interdisciplinary in nature, combining methodologies from many different fields, such as applied mathematics, engineering, and biology.

Specifically, systems science is concerned with developing new ways to look at complex systems, like the human brain. The identification, analysis, design, and control of such models are all part of this way of thinking. Examples of theories and models that have resulted from studies in systems science are chaos theory, neural networks, new organizational structures (such as holarchies), fuzzy logic, and artificial life. All of these things have their foundations in systems science.

Other fields of science have adopted this sytemic method of thought in their own applications. For instance, cognitive science is concerned with using systems to determine the behavior of the human brain. Environmental science uses chaos theory, and other systemic approaches, to try to model various aspects of the global environment, like the weather. Information science uses systems to help us understand the delivery and flow of information between nodes. And it would be irresponsible to omit the contributions of computer science to systems science, and vice versa. Computers are often used to play out the models that are founded in systems science. The use of neural networks in various contemporary software packages is but one example. To learn more about the various contributions of systems science, and its many sub-fields such as neural networks and artifical life, click here.

This field of study is particularly important to the field of environmental informatics. A large part of the study of the environmental information structural feedback loop is concerned with how to view such a system, and how to organize the system in such a way as to allow a suitable framework for decision making. Assuming that the environmental informatic structure is, at its most basic level, organized in the following way:

		    Action		
	Human  ----------------> Environment ---------------> Sensor
	    ^							|
	    |___________________________________________________| 	
				  Feedback

Systems science would be concerned with how to structure this framework in order to facilitate the easy flow of relevant information from the sensor to the human. The modeling, analysis, and control of the system is particularly important in reaching this goal. Therefore, it is clear that systems science plays an important role in the study of environmental informatics, as well as the issues discussed in this class.

Compiled by

Alex Olgilvie ~amo2@cec.wustl.edu Last updated 11/7/94.