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Ein Simulationsmodell für das Lösen rekursiver Programmierprobleme

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Maschinelles Lernen

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Zusammenfassung

Was zeichnet Experten vor Anfängern aus, was macht sie zu erfolgreicheren Problemlösern? Welches Wissen liegt ihrem Expertentum zugrunde und wie kann es zielführend beim Lösen neuer Probleme eingesetzt werden? Weshalb ist die Überlegenheit von Experten relativ eng auf den Gegenstandsbereich ihres Expertentums eingeschränkt?

Diese Arbeit wurde im Rahmen des Schwerpunktprogramms Wissenspsychologie durch die Deutsche Forschungsgemeinschaft unterstützt (Vo 212/2-4). — Erwin Gainer, Ursula Haack, Klaus Hahn, Dieter Heim, Hans Henning Schulze und Kai Wagner haben wesentliche Anteile an dieser Arbeit. Wir danken ihnen, Martin Heydemann, Otto Kühn, Franz Schmalhofer, Munira Schömann, Wolfgang Schwarz und Gerd Waloszek für anregende Diskussionen.

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Authors
  1. Rainer Goebel
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  2. Dirk Vorberg
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  1. Stedingerstraße 40, W-7000, Stuttgart 31, Deutschland

    Kristina Reiss  & Matthias Reiss  & 

  2. Karlstraße 86, W-7500, Karlsruhe 1, Deutschland

    Horst Spandl

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Goebel, R., Vorberg, D. (1992). Ein Simulationsmodell für das Lösen rekursiver Programmierprobleme. In: Reiss, K., Reiss, M., Spandl, H. (eds) Maschinelles Lernen. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77623-6_4

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  • DOI: https://doi.org/10.1007/978-3-642-77623-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55641-1

  • Online ISBN: 978-3-642-77623-6

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