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Dual Population Coding for Path Planning in Graphs with Overlapping Place Representations

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Spatial Cognition XII (Spatial Cognition 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12162))

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Abstract

Topological schemes for navigation from visual snapshots have been based on graphs of panoramic images and action links allowing the transition from one snapshot point to the next; see, for example, Cartwright and Collett [5] or Franz et al. [9]. These algorithms can only work if at each step a unique snapshot is recognized to which a motion decision is associated. Here, we present a population coding approach in which place is encoded by a population of overlapping “firing fields”, each of which is activated by the recognition of an unspecific “micro-snapshot” (i.e. feature), and associated to a subsequent action. Agent motion is then computed by a voting scheme over all activated snapshot-to-action associations. The algorithm was tested in a large virtual environment (Virtual Tübingen [24]) and shows biologically plausible navigational abilities.

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Notes

  1. 1.

    Unity Technologies, Unity 2018.1.5f1, https://unity3d.com/, 2018.

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Authors and Affiliations

  1. University of Tübingen, Tübingen, Germany

    Hanspeter A. Mallot, Gerrit A. Ecke & Tristan Baumann

Authors
  1. Hanspeter A. Mallot
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  2. Gerrit A. Ecke
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  3. Tristan Baumann
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Corresponding authors

Correspondence to Gerrit A. Ecke or Tristan Baumann .

Editor information

Editors and Affiliations

  1. University of Latvia, Riga, Latvia

    Jurǵis Šķilters

  2. Temple University, Philadelphia, PA, USA

    Nora S. Newcombe

  3. Northwestern University, Evanston, IL, USA

    David Uttal

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Mallot, H.A., Ecke, G.A., Baumann, T. (2020). Dual Population Coding for Path Planning in Graphs with Overlapping Place Representations. In: Šķilters, J., Newcombe, N., Uttal, D. (eds) Spatial Cognition XII. Spatial Cognition 2020. Lecture Notes in Computer Science(), vol 12162. Springer, Cham. https://doi.org/10.1007/978-3-030-57983-8_1

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  • DOI: https://doi.org/10.1007/978-3-030-57983-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57982-1

  • Online ISBN: 978-3-030-57983-8

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