Marc Jekel

What is adaptive about adaptive decision making? A parallel constraint satisfaction account ☆

There is broad consensus that human cognition is adaptive. However, the vital question of how exactly this adaptivity is achieved has remained largely open. Herein, we contrast two frameworks which account for adaptive decision making, namely broad and general single-mechanism accounts vs. multi-strategy accounts. We propose and fully specify a single-mechanism model for decision making based on parallel constraint satisfaction processes (PCS-DM) and contrast it theoretically and empirically against a multi-strategy account. To achieve sufficiently sensitive tests, we rely on a multiple-measure methodology including choice, reaction time, and confidence data as well as eye-tracking. Results show that manipulating the environmental structure produces clear adaptive shifts in choice patterns - as both frameworks would predict. However, results on the process level (reaction time, confidence), in information acquisition (eye-tracking), and from cross-predicting choice consistently corroborate single-mechanisms accounts in general, and the proposed parallel constraint satisfaction model for decision making in particular.

Victim Sensitivity and the Accuracy of Social Judgments

Recent theorizing on the relation between victim sensitivity and unethical behavior predicts that victim sensitivity is related to an asymmetrical focus on cues associated with untrustworthiness compared to cues associated with trustworthiness. This hypothesis and its consequences for the accuracy of social predictions are investigated in this article. In Study 1, participants rated the trustworthiness of 35 computer-animated faces that differed in their emotional expression. People high in victim sensitivity rated neutral and hostile faces more untrustworthy than people low in victim sensitivity, whereas no such effect was found for friendly faces. In Study 2, participants predicted the cooperativeness of 56 targets on the basis of minimal information. The accuracy of predictions was negatively related to victim sensitivity, and people high in victim sensitivity systematically underestimated targets’ cooperativeness. Thus, the asymmetrical focus on untrustworthiness cues among victim-sensitive individuals seems to impair rather than improve their social judgments.

A new and unique prediction for cue-search in a parallel-constraint satisfaction network model: The attraction search effect.

A common assumption of many established models for decision making is that information is searched according to some prespecified search rule. While the content of the information influences the termination of search, usually specified as a stopping rule, the direction of search is viewed as being independent of the valence of the retrieved information. We propose an extension to the parallel constraint satisfaction network model (iCodes: integrated coherence-based decision and search), which assumes—in contrast to prespecified search rules—that the valence of available information influences search of concealed information. Specifically, the model predicts an attraction search effect in that information search is directed toward the more attractive alternative given the available information. In 3 studies with participants choosing between two options based on partially revealed probabilistic information, the attraction search effect was consistently observed for environments with varying costs for information search although the magnitude of the effect decreased with decreasing monetary search costs. We also find the effect in reanalyses of 5 published studies. With iCodes, we propose a fully specified formal model and discuss implications for theory development within competing modeling frameworks.