Proceedings of the Annual Meeting of the Cognitive Science Society

Much of social cognition involves reasoning about others' minds: predicting their reactions, inferring their feelings, and explaining their behavior. By representing mental contents like beliefs, desires, and emotions, Bayesian theory of mind mod- els have made progress in capturing how humans manage these cognitive feats. But social life is not merely observation: hu- mans must also plan to intervene on these same mental con- tents. The present work models how people choose interven- tions to influence others' emotions. Building on a prior model of people's intuitive theory of emotions, we model how people use their intuitive theory to evaluate and simulate the effects of different interventions. We apply our model to data from behavioral experiments requiring counterfactual and joint in- terventions, and show a close alignment with human choices. Our results provide a step towards a potentially unifying expla- nation for emotion prediction and intervention, suggesting that they could arise from the same underlying generative model.