Evolving Brain Structures for Robot Control
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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