Development of goal-directed gaze shift based on predictive learning

Understanding others´ actions as goal-directed is a key mechanism to develop social cognitive abilities such as imitation and cooperation. Recent findings in psychology have demonstrated that the ability to predict the goal of observed actions emerges as early as six months in infancy. However, what mechanisms are involved and how they trigger the development of this ability are still open questions. In this paper, we propose a computational model employing a recurrent neural network to reproduce the developmental process of goal-directed gaze shift. Our hypothesis is that it is possible to infer the goal of observed actions by learning to predict the attention target originated from bottom-up visual attention. While keeping consistency with psychological findings, our experimental results confirmed the hypothesis that learning to predict the attention targets leads to the development of predictive gaze shift to the action goal.