The present invention relates to a method for learning task skills using temporal and spatial entropy. The method for learning task skills includes receiving, by a learning engine, an input of learning data on a given task and modeling the entire behavior path into a plurality of Gaussian using a Gaussian mixture model (GMM) according to the number of first parameters, calculating, by the learning engine, temporal and spatial entropy from the modeled Gaussian, extracting an intersection area by detecting a portion greater than or equal to a temporal threshold among temporal entropy and detecting a portion less than or equal to a spatial threshold among spatial entropy, by the learning engine, and dividing a behavior path for the extracted intersection area from the entire behavior path and modeling the divided behavior path using a GMM according to the number of second parameters.
METHOD FOR LEARNING TASK SKILL USING TEMPORAL AND SPATIAL ENTROPHIES