Obviously, when a model is put to practical use, its reliability is frequently doubtful.
The modeler should always be aware of the limits of the model's validity and, in consequence, revalidate it frequently: we should remember St. BEER warnings about the "surrogate world we manage" (1973).
Unfortunately, modelers, in many cases, do not recognize discrepancies and perturb heavily the concrete process or system by taking erroneous decisions and stick to them, even against strong evidence.
To avoid this, modelization should be iterative, as advocated by St. BEER. This is stated by J. ARACIL as follows: "The mechanism underlying the model should be frequently reviewed throughout the modeling process. These revisions are made in such a way that the successive models progressively fit in with the modeled object. The building up of a model is an iterative process where successive theoretical frameworks (normally re-elaborations of former ones) are adapted" (1986, p.243).
As a synthesis, iterative construction of models is a cybernetic process based on mental feedback.
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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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