Motor primitive and sequence self-organization in a hierarchical recurrent neural network

@article{Paine2004MotorPA,
  title={Motor primitive and sequence self-organization in a hierarchical recurrent neural network},
  author={Rainer W. Paine and Jun Tani},
  journal={Neural networks : the official journal of the International Neural Network Society},
  year={2004},
  volume={17 8-9},
  pages={1291-309}
}
This study describes how complex goal-directed behavior can be obtained through adaptation processes in a hierarchically organized recurrent neural network using a genetic algorithm (GA). Our experiments, using a simulated Khepera robot, showed that different types of dynamic structures self-organize in the lower and higher levels of the network for the purpose of achieving complex navigation tasks. The parametric bifurcation structures that appear in the lower level explain the mechanism of… CONTINUE READING
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