Proceedings of the Annual Meeting of the Cognitive Science Society

As we transition from child to adult, we navigate the worlddifferently. In this world, many of the relationships betweenevents are unclear or uncertain because they are probabilisticin nature. We wanted to know how learning about probabilis-tic relationships changes with development and to interrogatethe underlying processes. We investigated these questions in aprobabilistic reinforcement learning task (The Butterfly Task)with 302 participants aged 8-30. We found performance in thistask increased with age through early-twenties, then stabilized.Using hierarchical Bayesian methods to fit computational rein-forcement learning models, we showed that this performanceincrease was driven by 1) an increase in learning rate (i.e. de-crease in integration time horizon); 2) a decrease in exploratorychoices. By contrast, forgetting rates did not change with age.We discuss our findings in the context of other studies and hy-potheses about adolescent brain development.