Abstract
Recently, there have been many researches of robot partner for social communication. The robots should gather various type of information for communicating with people by using some internal sensors. However, it is difficult for the robots to gather the information by themselves because of the frame problem. Therefore, a system integrating sensor networks and portable sensing devices is required. The system should also have a platform for extracting and estimating the required information from the gathered data. In this paper, we applied a learning method based on the time series of data measured by sensor networks for estimating human behaviors. In the method, we propose a hierarchical learning structure based on spiking neural networks for modeling the human behavior patterns.
