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Modeling obstacle avoidance behavior of flies using an adaptive autonomous agent

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83985

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

http://pubman.mpdl.mpg.de/cone/persons/resource/persons83839

Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Huber, S., & Bülthoff, H. (1997). Modeling obstacle avoidance behavior of flies using an adaptive autonomous agent. Proceedings of the 7th International Conference on Artificial Neural Networks, ICANN 97, Lausanne, Switzerland, (Eds.) W. Gerstner et al. Springer Lecture Notes in Science, Berlin 1997, 709-714.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-E9D2-3
Zusammenfassung
In the course of evolution flies have developed specialized visuomotor programs for tasks like compensating for course deviations, obstacle avoidance, and tracking, which are based on the analysis of visual motion information. In order to test models of the obstacle avoidance behavior in flies, we use computer-simulated agents that evolve parts of their sensor system and sensorimotor coupling with genetic algorithms. During a simulated evolution, these agents specialize a visuomotor program that enables the agents to avoid obstacles.