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 netw orks of different sizes and architectures. Solutions for obstacle a voidance 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.
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© 2001 Springer-Verlag Berlin Heidelberg
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Pasemann, F., Steinmetz, U., Hülse, M., Lara2, B. (2001). Evolving Brain Structures for Robot Control. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_49
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DOI: https://doi.org/10.1007/3-540-45723-2_49
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