Prediction of Human Behavior Patterns based on Spiking Neurons for A Partner Robot

This paper discusses prediction of human behavior patterns for natural communication between a partner robot and a human. The prediction is very important to extract the perceptual information for the natural communication with a human in the future. Therefore we propose a prediction-based perceptual system based on spiking neurons. The proposed method is composed of four layers: the input layer, clustering layer, prediction layer, and perceptual module selection layer. In the clustering layer, an unsupervised learning method is used to perform the clustering of human behavior patterns. We use unsupervised learning because the human behavior patterns to be paid attention change by the other and the situation in communication. Furthermore, we show experimental results of the communication between a partner robot and a human based on our proposed method

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