Proceedings of the Annual Meeting of the Cognitive Science Society

Decision makers face a nontrivial problem when evaluating how much time to invest in an uncertain future prospect. Un- conditional persistence is not always advantageous; rather, different levels of persistence are favored in environments with different temporal statistics. Previous studies using foraging- like decision-making tasks have found that people can rapidly recalibrate their persistence behavior—becoming either more or less willing to tolerate delay—after a short period of direct experience with the temporal statistics of a new environment. Furthermore, substantial individual variation is apparent both in baseline levels of persistence and in the flexibility of re- calibration across environments. However, it is unknown to what degree such variation reflects trait-like individual differences in contrast to session-specific measurement noise. Here we investigated the test-retest reliability of individual variation in behavioral persistence in a computerized decision-making task. We conducted an online experiment in which participants (n=141 after exclusions) performed the task on two occasions separated by a three-week interval. We evaluated the test- retest reliability of several behavior-derived indices, including: a descriptive estimate of overall willingness to wait, a contrast measure reflecting flexibility of recalibration across environments, and individual-level parameter estimates derived from a reinforcement learning model of adaptive persistence. The results showed strong evidence for stable, trait-like individual variation in multiple aspects of persistence-related decision- making behavior. Our findings establish a foundation for future investigations of associations between task-derived parameters of decision behavior and other cognitive and motivational traits.