A computational approach to disentangling the triggers of curiosity in children and adults

If one important function of curiosity is to foster learning, what does curiosity direct agents to learn? The present research investigates what kinds of situations spark curiosity. Prior work has proposed many candidate triggers of curiosity, but they have rarely been disentangled in a single study. Using a Bayesian model applied to a trial-and-error learning task, we investigated the correspondence between optimal triggers of curiosity (those that maximize learning), heuristic triggers of curiosity (surprise and uncertainty), and participants’ reported curiosity. In Studies 1-2 (N = 848), adults’ curiosity was most sensitive to a “local” optimal trigger: how much would be learned about the immediate target of curiosity. Curiosity was less sensitive to heuristic triggers or a “global” optimal trigger: how much would be learned about broader learning goals. Study 3 (N = 310) showed that curiosity’s sensitivity to local learning was stronger in adults than in 5- to 9-year-olds. These studies suggest that curiosity is heightened by opportunities for learning about immediate targets of curiosity, but not always broader learning goals.