Development of compositional and contextual communicable congruence in robots by using dynamic neural network models

@article{Park2015DevelopmentOC,
  title={Development of compositional and contextual communicable congruence in robots by using dynamic neural network models},
  author={Gibeom Park and Jun Tani},
  journal={Neural networks : the official journal of the International Neural Network Society},
  year={2015},
  volume={72},
  pages={109-22}
}
The current study presents neurorobotics experiments on acquisition of skills for "communicable congruence" with human via learning. A dynamic neural network model which is characterized by its multiple timescale dynamics property was utilized as a neuromorphic model for controlling a humanoid robot. In the experimental task, the humanoid robot was trained to generate specific sequential movement patterns as responding to various sequences of imperative gesture patterns demonstrated by the… CONTINUE READING
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