Extensive research on probability learning has reported on the ubiquity of the probability matching strategy—choosing options in proportion to their probability of being correct. The current paper explores why the optimal strategy in this task (always choosing the higher probability option) is not intuitive for participants, by examining their decisions in relation to their working memory capacities. We hypothesize that probability matching is a by-product of an automatic recency-based strategy produced by limits in working memory storage and that deliberate strategizing mediated by working memory processing can override recency in favor of optimal responding. A variant of the Expectancy-Valence Learning Model is fit to participant data from a two-choice probability learning task using hierarchical Bayesian modelling. Point estimates of the best-fitting parameter values are then correlated with working memory measures. Results indicate close relations between them, providing support for our hypothesis.

Humans must often make decisions in temporally autoregressive environments (e.g., weather, stock market). Here, current states of the environment regress on their previous states (either across consecutive timesteps or from several timesteps back in a patterned fashion). The current work investigates people’s abilities to utilize previous states of autoregressive sequences as cues to its current state. In Experiment 1 we determine whether utilization of autoregressions reduces as the temporal distance of the predictive timestep increases; and in Experiment 2 we explore whether participants’ utilization of previous timesteps in predictions compete such that they reduce utilization of one timestep when increasing utilization of another timestep. We also fit data from both experiments with a trial-by-trial decision model. Overall, we find that participants significantly reduced utilization of a cue with its increased temporal distance. However, we obtained less conclusive results on competition among timestep cues. These results can explain people’s predictions in sequential decision tasks (e.g., their tendencies to perceive clumpiness in random environments).

Recency effects—giving exaggerated importance to recent outcomes—are a common aspect of decision tasks. In the current study, we explore two explanations of recency-based decision making, that it is (1) a deliberate strategy for adaptive decision making in real-world environments which tend to be dynamic and autocorrelated, and/or (2) a product of processing limitations of working memory. Supporting explanation 1, we found that participants strategically adjusted their recency levels across trials to achieve optimal levels in a range of tasks. Furthermore, they started with default recency values that had high aggregate performance across environments. However, only some correlations between recency values and WM scores were significant, providing no clear conclusion regarding explanation 2. Ultimately, we propose that recency involves a combination of the two—people can strategically change recency within the limits of WM capacities to adapt to external environments.

The choice to enter and leave a romantic relationship can be framed as a decision-making problem based on expected utility of the partnership over time, akin to a forager deciding whether to stay in a particular patch based on the amount of resources it provides. We examined the temporal trajectory of three traits that may correspond to resources in romantic relationships—trust, love, and satisfaction—to determine whether they behave like depleting or replenishing patches from a foraging perspective. All three rise over time in intact relationships—suggesting replenishment—but plateau or fall in dissolved relationships—suggesting depletion. Survival analysis demonstrated that higher ratings of all three quality variables decreased the risk of romantic dissolution. The results suggest that these cues are lower in dissolved relationships, indicating individuals could potentially use them as cues for leaving an unsatisfactory relationship patch via aspiration-level cognitive mechanisms.