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Context-based cognitive map learning for an autonomous robot using a model of cortico-hippocampal interplay

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Yasuhara,  K
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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

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Citation

Yasuhara, K., & Mallot, H. (1996). Context-based cognitive map learning for an autonomous robot using a model of cortico-hippocampal interplay. In C. von der Malsburg, W. von Seelen, J. Vorbrüggen, & B. Sendhoff (Eds.), Artificial Neural Networks: ICANN 96: 1996 International Conference Bochum, Germany, July 16–19, 1996 (pp. 623-628). Berlin, Germany: Springer.


Cite as: http://hdl.handle.net/21.11116/0000-0005-EA50-9
Abstract
This paper presents an additional module of cortico-hippocampal interplay to our view-based competitive sequence learning scheme of spatial memory. This new model was examined with a mobile robot. In this model both the orthogonalization of input patterns and the integration of object and spatial information are realized by use of a middle-term memory module as a model of hippocampal function. This scheme works well not only for orthogonal input views but also for highly correlated patterns. Even after the memory module is damaged, the robot can take the shortest path to the goal point if enough knowledge has been acquired prior to the damage.