We present an unsupervised learning method that allows a situated embodied agent to identify and represent qualitatively diierent experiences. The occurrence of events, such as the initiation of a particular action, triggers the collection of multivariate time series of sensor values. Those time series are clustered using Dynamic Time Warping as a measure of similarity , and prototypes are extr...
