title: Satisficing in split-second decision making is characterized by strategic cue discounting.
abstract: Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. It is thought that humans overcome these limitations through satisficing, fast but "good-enough" heuristic decision making that prioritizes some sources of information (cues) while ignoring others. However, the decision-making strategies we adopt under uncertainty and time pressure, for example during emergencies that demand split-second choices, are presently unknown. To characterize these decision strategies quantitatively, the present study examined how people solve a novel multicue probabilistic classification task under varying time pressure, by tracking shifts in decision strategies using variational Bayesian inference. We found that under low time pressure, participants correctly weighted and integrated all available cues to arrive at near-optimal decisions. With increasingly demanding, subsecond time pressures, however, participants systematically discounted a subset of the cue information by dropping the least informative cue(s) from their decision making process. Thus, the human cognitive apparatus copes with uncertainty and severe time pressure by adopting a "drop-the-worst" cue decision making strategy that minimizes cognitive time and effort investment while preserving the consideration of the most diagnostic cue information, thus maintaining "good-enough" accuracy. This advance in our understanding of satisficing strategies could form the basis of predicting human choices in high time pressure scenarios. (PsycINFO Database Record
authors.affiliation: Department of Psychology and Neuroscience, Duke University.
authors.forename: Hanna
authors.initials: H
authors.lastname: Oh
authors.affiliation: Department of Neurobiology, Duke University.
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Beck
authors.affiliation: Department of Mechanical and Aerospace Engineering, Cornell University.
authors.forename: Pingping
authors.initials: P
authors.lastname: Zhu
authors.affiliation: Department of Biomedical Engineering, Duke University.
authors.forename: Marc A
authors.initials: MA
authors.lastname: Sommer
authors.affiliation: Department of Mechanical and Aerospace Engineering, Cornell University.
authors.forename: Silvia
authors.initials: S
authors.lastname: Ferrari
authors.affiliation: Department of Psychology and Neuroscience, Duke University.
authors.forename: Tobias
authors.initials: T
authors.lastname: Egner
mesh_terms: D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D001499:Bayes Theorem; D003463:Cues; D003657:Decision Making; D005260:Female; D006801:Humans; D007600:Judgment; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011336:Probability; D011581:Psychological Tests; D011930:Reaction Time; D013315:Stress, Psychological; D013997:Time Factors; D055815:Young Adult