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Kwon, Oh-Sang
Perception & Action Lab
Research Interests
  • Aging, Visual perception, Human motor control, Statistical learning, Bayesian inference


Subjective optimality in finite sequential decision-making

DC Field Value Language Sin, Yeonju ko Seon, HeeYoung ko Shin, Yun Kyoung ko Kwon, Oh-Sang ko Chung, Dongil ko 2021-12-24T00:43:21Z - 2021-12-17 ko 2021-12 ko
dc.identifier.citation PLOS COMPUTATIONAL BIOLOGY, v.17, no.12, pp.e1009633 ko
dc.identifier.issn 1553-734X ko
dc.identifier.uri -
dc.description.abstract Author summaryIn many real-life decisions, such as hiring an employee, the current candidate is the only option decision-makers can choose among sequentially revealed options, while past options are forgone and future options are unknown. To make the best choice in such problems, decision-makers should set appropriate criteria considering the distribution of values and remaining chances. Here, we provide behavioral and physiological evidence for subjective valuation that explains how individuals set criteria deviating from optimality. The extent to which individuals expect from candidates, how sensitive they are to the value of candidates, and how costly it is to examine each candidate determine the way how individuals make choices. Our results suggest that seemingly suboptimal decision strategies in finite sequential decisions may be optimal in subjective valuation. Many decisions in life are sequential and constrained by a time window. Although mathematically derived optimal solutions exist, it has been reported that humans often deviate from making optimal choices. Here, we used a secretary problem, a classic example of finite sequential decision-making, and investigated the mechanisms underlying individuals' suboptimal choices. Across three independent experiments, we found that a dynamic programming model comprising subjective value function explains individuals' deviations from optimality and predicts the choice behaviors under fewer and more opportunities. We further identified that pupil dilation reflected the levels of decision difficulty and subsequent choices to accept or reject the stimulus at each opportunity. The value sensitivity, a model-based estimate that characterizes each individual's subjective valuation, correlated with the extent to which individuals' physiological responses tracked stimuli information. Our results provide model-based and physiological evidence for subjective valuation in finite sequential decision-making, rediscovering human suboptimality in subjectively optimal decision-making processes. ko
dc.language 영어 ko
dc.publisher Public Library of Science ko
dc.title Subjective optimality in finite sequential decision-making ko
dc.type ARTICLE ko
dc.identifier.wosid 000731436300004 ko
dc.type.rims ART ko
dc.identifier.doi 10.1371/journal.pcbi.1009633 ko
dc.identifier.url ko
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