Prediction and Prescription in Systems Modeling
Abstract
In modeling, as in any other human activity, there is a certain amount of historical inertia. Predictive models bulked large in the early history of modeling. In our enthusiastic efforts to explore the potential of computers we tended to conceptualize computers as numbers crunchers, and were not immediately able to see the potential for qualitative and symbolic modeling that did not use numbers. Before we begin a modeling task we need to answer the following: Whether we need temporal detail, and if so, what amount can be supported by the kinds of data and theories that we have available; whether a good understanding of steady states may be more important to us than tracing paths; whether we can simplify the systems we are modeling by making use of hierarchial properties to aggregate, or in other ways; are there aspects of the situation of interest that are better modeled symbolically, in words or pictures, rather than numerically? Keywords: Modeling complex systems; Nonlinear systems; Chaos.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 30, 1988
- Accession Number
- ADA219112
Entities
People
- Herbert Simon
Organizations
- Carnegie Mellon University