Can We Teach What Emotions a Robot should Express?

This paper presents a possibility that we can teach what emotions a robot should express. For this, we design an artificial emotion decision system learned by feedbacks of users. The proposed system consists of three parts: a personality space with probability model, an emotion decision process, and an emotion learning process. 1) The personality space is designed based on the Five-Factor Model. In the personality space, we set up probability distributions of emotions. 2) The emotion decision process determines the probability values of emotions using the probability distributions of emotions in the personality space. 3) The emotion learning process updates the probability distributions by the feedbacks that are the teaching information from users; then, different probability values of emotions are determined. By applying to a humanoid robot system, we have verified the validity of the proposed system by being learned from two persons who have different personalities.