Adaptive decision making in a dynamic environment: A test of a sequential sampling model of relative judgment.

Abstract

Research has identified a wide range of factors that influence performance in relative judgment tasks. However, the findings from this research have been inconsistent. Studies have varied with respect to the identification of causal variables and the perceptual and decision-making mechanisms underlying performance. Drawing on the ecological rationality approach, we present a theory of the judgment and decision-making processes involved in a relative judgment task that explains how people judge a stimulus and adapt their decision process to accommodate their own uncertainty associated with those judgments. Undergraduate participants performed a simulated air traffic control conflict detection task. Across two experiments, we systematically manipulated variables known to affect performance. In the first experiment, we manipulated the relative distances of aircraft to a common destination while holding aircraft speeds constant. In a follow-up experiment, we introduced a direct manipulation of relative speed. We then fit a sequential sampling model to the data, and used the best fitting parameters to infer the decision-making processes responsible for performance. Findings were consistent with the theory that people adapt to their own uncertainty by adjusting their criterion and the amount of time they take to collect evidence in order to make a more accurate decision. From a practical perspective, the paper demonstrates that one can use a sequential sampling model to understand performance in a dynamic environment, allowing one to make sense of and interpret complex patterns of empirical findings that would otherwise be difficult to interpret using standard statistical analyses.

Evidence accumulation in a complex task: Making choices about concurrent multiattribute stimuli under time pressure.

“…It is possible that air traffic controllers may respond to an increase in workload caused by new aircraft entering the sector, or aircraft requesting diversion around weather, by adjusting their rate (i.e., by working faster). They may only adjust their threshold as they approach their capacity limit (Loft, Bolland, Humphreys, & Neal, 2009;Neal et al, 2013). Figure 10.…”

Strategic attention and decision control support prospective memory in a complex dual-task environment

“…Table 2 gives the range of values for the features of aircraft pairs and the distribution they were drawn from. We fixed the angle of approach between aircraft at 90 degrees to avoid interactions between angle and perceived conflict status (e.g., Vuckovic, Kwantes, & Neal, 2013). The flight level for all aircraft was fixed at 37,000 feet.…”

Choice Under Risk: How Occupation Influences Preferences

“…It is plausible that occupational background facilitates learning of behavioral decision strategies, which influences risk preferences and dominates the sensitivity to contextually presented probabilistic information (e.g., Dayan and Daw, 2008; Vuckovic et al, 2013). Therefore, in this study, our aim is to investigate the influence of type of occupation and decision-making framing [e.g., variations in decision domain (loss and gain; Tversky and Kahneman, 1981), context, presentation of risk and utility ratios] on risk preferences.…”