기본 정보
연구 분야
프로젝트
논문
구성원
preprint|
green
·인용수 1
·2020
Subjective optimality in finite sequential decision-making
Yeonju Shin, HeeYoung Seon, Yun Kyoung Shin, Oh‐Sang Kwon, Dongil Chung
bioRxiv (Cold Spring Harbor Laboratory)
초록

Abstract 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 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.

키워드
Valuation (finance)Optimal decisionBellman equationComputer scienceStimulus (psychology)Dynamic programmingPsychologyCognitive psychologyMathematical optimizationArtificial intelligence
타입
preprint
IF / 인용수
- / 1
게재 연도
2020