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 models have made progress in capturing how humans manage these cognitive feats. But social life is not merely observation: humans must also plan to intervene on these same mental contents. The present work models how people choose interventions 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 interventions, and show a close alignment with human choices. Our results provide a step towards a potentially unifying explanation for emotion prediction and intervention, suggesting that they could arise from the same underlying generative model.
