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Erschienen in:
1999 | OriginalPaper | Buchkapitel
Nonuniqueness, Uncertainty, and Complexity in Modeling
verfasst von : Hidenori Kimura
Erschienen in: Applied and Computational Control, Signals, and Circuits
Verlag: Birkhäuser Boston
Enthalten in: Professional Book Archive
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The modeling is essentially an ill-posed problem in the sense that the data cannot determine the model of the real world uniquely. This chapter discusses the modeling issues from the nonuniqueness point of view, and proposes to keep the nonuniqueness as an explicit representation of the incompleteness of our knowledge and information. This naturally leads to the notion of model set. System theory of model set is proposed as an approach to establish the formal theory of models and modeling that resolves various issues of modeling. Complexity of the real world and the model is discussed from the viewpoint of model set. Also, it is shown that learning is most suitably formulated in the framework of model set.