IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v16y2010i3d10.1007_s10588-010-9073-3.html
   My bibliography  Save this article

A cognitive model of spatial path-planning

Author

Listed:
  • David Reitter

    (Carnegie Mellon University)

  • Christian Lebiere

    (Carnegie Mellon University)

Abstract

Planning a path to a destination, given a number of options and obstacles, is a common task. We suggest a two-component cognitive model that combines retrieval of knowledge about the environment with search guided by visual perception. In the first component, subsymbolic information, acquired during navigation, aids in the retrieval of declarative information representing possible paths to take. In the second component, visual information directs the search, which in turn creates knowledge for the first component. The model is implemented using the ACT-R cognitive architecture and makes realistic assumptions about memory access and shifts in visual attention. We present simulation results for memory-based high-level navigation in grid and tree structures, and visual navigation in mazes, varying relevant cognitive (retrieval noise and visual finsts) and environmental (maze and path size) parameters. The visual component is evaluated with data from a multi-robot control experiment, where subjects planned paths for robots to explore a building. We describe a method to compare trajectories without referring to aligned points in the itinerary. The evaluation shows that the model provides a good fit, but also that planning strategies may vary with task loads.

Suggested Citation

  • David Reitter & Christian Lebiere, 2010. "A cognitive model of spatial path-planning," Computational and Mathematical Organization Theory, Springer, vol. 16(3), pages 220-245, September.
    • Handle: RePEc:spr:comaot:v:16:y:2010:i:3:d:10.1007_s10588-010-9073-3
    DOI: 10.1007/s10588-010-9073-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-010-9073-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10588-010-9073-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lanny Lin & Michael A. Goodrich, 2010. "A Bayesian approach to modeling lost person behaviors based on terrain features in Wilderness Search and Rescue," Computational and Mathematical Organization Theory, Springer, vol. 16(3), pages 300-323, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Changkun Zhao & Ryan Kaulakis & Jonathan H. Morgan & Jeremiah W. Hiam & Frank E. Ritter & Joesph Sanford & Geoffrey P. Morgan, 2015. "Building social networks out of cognitive blocks: factors of interest in agent-based socio-cognitive simulations," Computational and Mathematical Organization Theory, Springer, vol. 21(2), pages 115-149, June.
    2. Frank E. Ritter & William G. Kennedy & Bradley J. Best, 2013. "The best papers from BRIMS 2011: models of users and teams interacting," Computational and Mathematical Organization Theory, Springer, vol. 19(3), pages 283-287, September.
    3. Minaei, Negin, 2014. "Do modes of transportation and GPS affect cognitive maps of Londoners?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 162-180.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Frank E. Ritter & William G. Kennedy & Bradley J. Best, 2013. "The best papers from BRIMS 2011: models of users and teams interacting," Computational and Mathematical Organization Theory, Springer, vol. 19(3), pages 283-287, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:comaot:v:16:y:2010:i:3:d:10.1007_s10588-010-9073-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.