Learning Emotion Regulation Strategies: A Cognitive Agent Model

Learning to cope with negative emotions is an important challenge, which has received considerable attention in domains like the military and law enforcement. Driven by the aim to develop better training in coping skills, this paper presents an adaptive computational model of emotion regulation strategies, which is inspired by recent neurological literature. The model can be used both to gain more insight in emotion regulation training itself and to develop intelligent virtual reality-based training environments. The behaviour of the model is illustrated by a number of simulation experiments and by a mathematical analysis. In addition, a preliminary validation points out that it is able to approximate empirical data obtained from an experiment with human participants.