@inproceedings{e98005766f2948bb9571d1ea2840123e,
title = "Minimalistic approach to 3D obstacle avoidance behavior from simulated evolution",
abstract = "We present a minimalistic approach to establish obstacle avoidance and course stabilization behavior of a simulated flying autonomous agent in a 3D virtual world. The agent uses visual cues, and its sensory and motor components arc based on biological principles found in flies. A simple neural network is used for coupling the receptor and effector systems of the agent. In order to achieve appropriate reactions to sensory input, the connection weights are adjusted by a genetic algorithm under a closed loop action-perception condition.",
author = "Neumann, {Titus R.} and Huber, {Susanne A.} and B{\"u}lthoff, {Heinrich H.}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1997.; 7th International Conference on Artificial Neural Networks, ICANN 1997 ; Conference date: 08-10-1997 Through 10-10-1997",
year = "1997",
doi = "10.1007/bfb0020238",
language = "English",
isbn = "3540636315",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "715--720",
editor = "Wulfram Gerstner and Alain Germond and Martin Hasler and Jean-Daniel Nicoud",
booktitle = "Artificial Neural Networks - ICANN 1997 - 7th International Conference, Proceeedings",
}