COMPUTER MODELS 1)3)
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G. KLIR states: "As a rule, genuine system problems are computationally extremely difficult. They are often made tractable by overly strong simplifying assumptions that are usually not explicitely stated. The resulting methods can then deal with sizeable systems emerging from practical application and produce "impressive" results, but the significance of these results is questionable at best. Such methodological dishonesty is contrary to the spirit of systems science, The latter is not interested in producing immediately marketable methodological tools at the cost of convenient simplifying assumptions whose validity is dubious, but rather in pursuing basic methodological research involving genuine systems problems" (1993, p.50).
KLIR proposes better uses of computers in systems science, (see above).
For D. MEADOWS and her collaborators different but not contradictory views, see Model (Computer)
Categories
- 1) General information
- 2) Methodology or model
- 3) Epistemology, ontology and semantics
- 4) Human sciences
- 5) Discipline oriented
Publisher
Bertalanffy Center for the Study of Systems Science(2020).
To cite this page, please use the following information:
Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]
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