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Context-based cognitive map learning for an autonomous robot using a model of cortico-hippocampal interplay

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Artificial Neural Networks — ICANN 96 (ICANN 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1112))

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Abstract

This paper presents an additional module of cortico-hippocampal interplay to our view-based competitive sequence learning scheme of spatial memory. This new model was examined with a mobile robot. In this model both the orthogonalization of input patterns and the integration of object and spatial information are realized by use of a middle-term memory module as a model of hippocampal function. This scheme works well not only for orthogonal input views but also for highly correlated patterns. Even after the memory module is damaged, the robot can take the shortest path to the goal point if enough knowledge has been acquired prior to the damage.

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References

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Author information

Authors and Affiliations

  1. Max-Planck-Institut für biologische Kybernetik, Spemannstr.38, 72076, Tübingen, Germany

    Ken Yasuhara & Hanspeter A. Mallot

Authors
  1. Ken Yasuhara
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  2. Hanspeter A. Mallot
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Editor information

Christoph von der Malsburg Werner von Seelen Jan C. Vorbrüggen Bernhard Sendhoff

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© 1996 Springer-Verlag Berlin Heidelberg

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Yasuhara, K., Mallot, H.A. (1996). Context-based cognitive map learning for an autonomous robot using a model of cortico-hippocampal interplay. In: von der Malsburg, C., von Seelen, W., Vorbrüggen, J.C., Sendhoff, B. (eds) Artificial Neural Networks — ICANN 96. ICANN 1996. Lecture Notes in Computer Science, vol 1112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61510-5_106

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  • DOI: https://doi.org/10.1007/3-540-61510-5_106

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61510-1

  • Online ISBN: 978-3-540-68684-2

  • eBook Packages: Springer Book Archive

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