Motivational Emotion Generation and Behavior Selection based on Emotional Experiences for Social Robots

Abstract

As the number of social and psychological service robots increase, many robots which have emotions have been developed. In order to implement an emotion generation model, the authors of this paper suggest to employ the unified motivation theory which is proposed by Higgins. In addition, a behavior selection model based on emotional experience is suggested. A joint attention scenario is suggested in which a human and a robot play a 2048 game together with a follow-up interaction. A preliminary pilot test was conducted to examine the proposed method and it performed properly as intended. Finally, further experiment plans and expectations are discussed.