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Solving for Two Unknowns: An Extension of Vector-based Models of Landmark-based Navigation
Journal of Experimental Psychology: Animal Behavior Processes (2011)
  • Bradley R. Sturz, Georgia Southern University
  • Paul S. Cooke
  • Kent D. Bodily
Abstract
Vectors are mathematical representations of distance and direction information that take the form of line segments where length represents distance and orientation in space represents direction. Vector-based models have proven beneficial in understanding the spatial behavior of a variety of species in tasks that require landmark-based navigation via vector addition and vector averaging to determine a location. Extant research regarding vector-based representational and computational accounts of landmark-based navigation has involved tasks that required solving for one unknown (i.e., a location). Using a novel landmark-based navigation task, we provide evidence consistent with a form of vector algebra that involves solving two simultaneous equations with two unknowns in order to determine a location in space. Results extend vector-based accounts of landmark-based navigation and provide a novel methodological approach to the testing of mobile organisms.
Keywords
  • Virtual environment,
  • Spatial learning,
  • Navigation,
  • Vector algebra,
  • Cognitive evolution
Disciplines
Publication Date
July, 2011
Citation Information
Bradley R. Sturz, Paul S. Cooke and Kent D. Bodily. "Solving for Two Unknowns: An Extension of Vector-based Models of Landmark-based Navigation" Journal of Experimental Psychology: Animal Behavior Processes Vol. 37 Iss. 3 (2011)
Available at: http://works.bepress.com/bradley_sturz/95/