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The paper aims at: a) showing that approximation and undecidability refer to entirely different and incommensurable kinds of uncertain knowledge processing and have non-intersecting application domains; b) exposing the shortcomings of conservative approaches (including approximation theory) for treating "real-world undecidability" in applications meant for open, dynamic, and uncertain environments (first of all where modelling decision-making is concerned); c) outlining the rationale and the approach (based on bounded rationality) to deal with all kinds of uncertainty arising in economic modelling. (The mechanisms involved are only briefly suggested, being described in papers referred to.) Among the conclusions: approximation is still a valuable asset in modelling but mainly aiming at effectiveness, not at uncertain knowledge processing, because of its atemporality (mainly its ineffectiveness in dealing with future events); the bounded-rationality approach proposed in this paper enables both better economic models and better modelling (being based on trends in economic modelling as well as on agent-oriented software engineering).