Delayed Planning in Human Decision Making

Planning is an expensive computational operation that easily exhausts our cognitive resources. For this reason, it is critical to learn strategies to initiate planning wisely. Although recent advances have shown where and how planning should be engaged to aid adaptive behavior, little is known about when planning should be engaged. Here, we investigate how individuals choose to engage or delay planning. For this purpose, we developed a task where, at certain decision points in a multistep decision problem, it is optimal to delay planning and relinquish control because all actions are equally likely to reach an instructed goal. Across two studies, we show that humans can optimally delay planning and improve in their ability to do so with experience. To explain this behavior, we formalize a model of the underlying meta-control computations. In doing so, we demonstrate that meta-policies to engage or delay planning are not simply learned from experienced outcomes, rather, they are constructed by searching a cognitive map of the task to determine at which points it is more valuable to delay control. We thus establish that humans can optimally delay planning, and learn to do so by means of a cognitive map.