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A cognitive model of spatial path-planning

Author

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  • 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
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    References listed on IDEAS

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    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.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.

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    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.

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