Proceedings of the Annual Meeting of the Cognitive Science Society

When people plan, they often do so in the face of uncertainty. However, little is known about how uncertainty affects planning. To study these effects, we used a reward gathering task in which the we varied the reliability of announced rewards varied from certain to completely random. We quantitatively compared several planning models. We found that participants used a suboptimal approach, failing to directly incorporate stochasticity into their planning. Instead, they "compensated" for uncertainty by decreasing their planning effort as stochasticity increased. First-move response time correspondingly decreased with increasing stochasticity. Our findings generalized to a manipulation of transition uncertainty. Together, these findings open the door to a more comprehensive and computationally grounded understanding of the role of stochasticity in planning.