Abstract
The objective of this work is to modelize the evolution of a Model-System to be adapted to a Random System. This evolution is described by means of the change of a probabilistic function, through deterministic rules and in function of the random responses of the modelized System. This probabilistic function can describe the relative weight of distinct submodels (deterministic or random Systems, with constant or variable stimulus), or the stimulus-response relation in the Model-System (Adaptative Random System). We conclude that the Adaptative Random Model permits a more precise, simple and economical modelling.
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© 1986 D. Reidel Publishing Company
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Pla-López, R. (1986). Models of Dynamical Modelling Under Uncertainty. In: Trappl, R. (eds) Cybernetics and Systems ’86. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-4634-7_15
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DOI: https://doi.org/10.1007/978-94-009-4634-7_15
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-8560-1
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