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Recognition-Triggered Response and the View-Graph Approach to Spatial Cognition

MPG-Autoren
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Mallot,  HA
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Gillner,  S
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Steck,  SD
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Franz,  MO
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Mallot, H., Gillner, S., Steck, S., & Franz, M. (1999). Recognition-Triggered Response and the View-Graph Approach to Spatial Cognition. In International Conference on Spatial Information Theory: Cognitive and Computational Foundations of Geographic Information Science (COSIT '99) (pp. 367-380). Berlin, Germany: Springer.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-E66F-E
Zusammenfassung
The simplest representation of space allowing for spatial cognition in biological and artificial systems is a graph; the nodes of this graph contain local position information (views) chracterizing certain places while its links are labeled with movements or actions leading from one view to the next. In this paper, we review recent theoretical and psychological 2ork on view-graph representations. In particular, we will focus on the transition from stereotyped "recognition-triggered responses" to a graph-like cognitive map where the recognition of a view allows to choose one of several responses. We will present psychophysical evidence from experiments using virtual reality indicating that human subjects do make use of simple view-movement associations without recognizing places. This mechanism is not restricted to navigation in mazes but can be extended to large-scale open environments by means of an additional guidance mechanism. As compared to more map-like approaches such as occupancy grids or survey-maps, the view-graph is less computationally expensive and can easily be adapted to the coarseness of spatial knowledge.