Managing Complex Systems: An Application of Ensemble Methods in System Theory
The increasing complexity of modern life means that science, along with society, must increasingly deal with complex problems. While some sciences and most professions deal with complexity in more than a passing way, the system sciences are decisively, almost by definition, sciences of complexity. This aspect of their nature follows from their emphasis on “systems,” i.e., things seen in their functional wholeness. In attending to completeness, the system sciences must necessarily disavow the tactic common in discipline-centered inquiries, namely that of redefining a problem so as to make it approachable. System science therefore shares with the professions (and other real-world activities) an unavoidable confrontation with complexity.
KeywordsSystem Science Force Input Internal Homogeneity Simple Network Model Logical Probability Model
Unable to display preview. Download preview PDF.
- 1.Ashby, W. Ross, Design for a Brain, 1960, New York: Wiley.Google Scholar
- 2.Babcock, A.K., “Logical Probability Models and Representation Theorems on the Stable Dynamics of the Genetic Net,” Doctoral Dissertation, University of New York at Buffalo, 1976.Google Scholar
- 3.Dertouzos, Michael, Threshold Logic: A Synthesis Approach, 1966, MIT Press: Cambridge.Google Scholar
- 4.Gelfand, Alan E. and Walker, Crayton C., “Management Strategies in Fixed-Structure Models of Complex Organizations II.” Forthcoming technical report, ONR Contract N000–14–76-C-0475, Department of Statistics, Stanford University, Stanford, California.Google Scholar
- 6.Kauffman, S.A., “The Organization of Cellular Genetic Control Systems,” 1970, Math. in the Life Sciences 3: 63–116.Google Scholar
- 9.Walker, Crayton C. and Gelfand, Alan E., “Management Strategies in Fixed-Structure Models of Complex Organizations,” March 14, 1977. Technical Report No. 243, ONR Contract N00014–76-C-0475, Department of Statistics, Stanford University, Stanford, California.Google Scholar