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MiS Preprint
20/2001

Evolving brain structures for robot control

Frank Pasemann, Ulrich Steinmetz, Martin Hülse and Bruno Lara

Abstract

To study the relevance of recurrent neural network structures for the behavior of autonomous agents a series of experiments with miniature robots is performed. A special evolutionary algorithm is used to generate networks of different sizes and architectures. Solutions for obstacle avoidance and phototropic behavior are presented. Networks are evolved with the help of simulated robots, and the results are validated with the use of physical robots.

Received:
Apr 4, 2001
Published:
Apr 4, 2001

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inBook
2001 Repository Open Access
Frank Pasemann, Ulrich Steinmetz, Martin Hülse and Bruno Lara

Evolving brain structures for robot control

In: 6th International Work Conference on Artificial and Natural Neural Networks / José Mira (ed.)
Berlin ; Heidelberg ; New York ; Barcelona ; Hong Kong ; London : Springer, 2001. - pp. 410-417
(Lecture notes in computer science ; 2085)