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A Cognitive Model That Describes the Influence of Prior Knowledge on Concept Learning

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Artificial Neural Networks – ICANN 2007 (ICANN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4669))

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Abstract

It is well known that our prior knowledge and experiences affect how we learn new concepts. Although several formal modeling attempts have been made to quantitatively describe the mechanisms about how prior knowledge influences concept learning behaviors, the underlying cognitive mechanisms that give rise to the prior knowledge effects remains unclear. In this paper, we introduce a computational cognitive modeling framework that is intended to describe how prior knowledge and experiences influence learning behaviors. In particular, we assume that it is not simply the prior knowledge stored in our memory trace influencing our behaviors, but it is also the learning strategies acquired through previous learning experiences that affect our learning behaviors. Two simulation studies were conducted and the results showed promising outcomes.

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Joaquim Marques de Sá Luís A. Alexandre Włodzisław Duch Danilo Mandic

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© 2007 Springer-Verlag Berlin Heidelberg

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Matsuka, T., Sakamoto, Y. (2007). A Cognitive Model That Describes the Influence of Prior Knowledge on Concept Learning. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D. (eds) Artificial Neural Networks – ICANN 2007. ICANN 2007. Lecture Notes in Computer Science, vol 4669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74695-9_93

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  • DOI: https://doi.org/10.1007/978-3-540-74695-9_93

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74693-5

  • Online ISBN: 978-3-540-74695-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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