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  Modeling obstacle avoidance behavior of flies using an adaptive autonomous agent

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.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E9D2-3 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E9D3-1
Genre: Conference Paper

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 Creators:
Huber, S1, Author           
Bülthoff, HH1, Author           
Gerstner, Editor
W., Editor
Germond, A., Editor
Hasler, M., Editor
Nicoud, J.-D., Editor
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              

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 Abstract: 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.

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 Dates: 1997-10
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: ISBN: 3-540-63631-5
URI: http://www.springerlink.com/content/ml2388231u7v5153/fulltext.pdf
DOI: 10.1007/BFb0020237
BibTex Citekey: 363
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Title: 7th International Conference on Artificial Neural Networks
Place of Event: Lausanne, Switzerland
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Title: 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
Source Genre: Journal
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Affiliations:
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 709 - 714 Identifier: -