Time Pressure Changes How People Explore and Respond to Uncertainty

Overview

Journal Sci Rep

Specialty Science

Date 2022 Mar 9

PMID 35260717

Authors

Charley M Wu

Eric Schulz

Timothy J Pleskac

Maarten Speekenbrink

Affiliations

Soon will be listed here.

Abstract

How does time pressure influence exploration and decision-making? We investigated this question with several four-armed bandit tasks manipulating (within subjects) expected reward, uncertainty, and time pressure (limited vs. unlimited). With limited time, people have less opportunity to perform costly computations, thus shifting the cost-benefit balance of different exploration strategies. Through behavioral, reinforcement learning (RL), reaction time (RT), and evidence accumulation analyses, we show that time pressure changes how people explore and respond to uncertainty. Specifically, participants reduced their uncertainty-directed exploration under time pressure, were less value-directed, and repeated choices more often. Since our analyses relate uncertainty to slower responses and dampened evidence accumulation (i.e., drift rates), this demonstrates a resource-rational shift towards simpler, lower-cost strategies under time pressure. These results shed light on how people adapt their exploration and decision-making strategies to externally imposed cognitive constraints.

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References

Bogacz R, Wagenmakers E, Forstmann B, Nieuwenhuis S . The neural basis of the speed-accuracy tradeoff. Trends Neurosci. 2009; 33(1):10-6. DOI: 10.1016/j.tins.2009.09.002. View

Sanborn A, Griffiths T, Navarro D . Rational approximations to rational models: alternative algorithms for category learning. Psychol Rev. 2010; 117(4):1144-67. DOI: 10.1037/a0020511. View

Schulz E, Gershman S . The algorithmic architecture of exploration in the human brain. Curr Opin Neurobiol. 2018; 55:7-14. DOI: 10.1016/j.conb.2018.11.003. View

Wilson R, Bonawitz E, Costa V, Ebitz R . Balancing exploration and exploitation with information and randomization. Curr Opin Behav Sci. 2020; 38:49-56. PMC: 7654823. DOI: 10.1016/j.cobeha.2020.10.001. View

Gershman S . Uncertainty and Exploration. Decision (Wash D C ). 2021; 6(3):277-286. PMC: 7989061. DOI: 10.1037/dec0000101. View

Wu C, Schulz E, Speekenbrink M, Nelson J, Meder B . Generalization guides human exploration in vast decision spaces. Nat Hum Behav. 2019; 2(12):915-924. DOI: 10.1038/s41562-018-0467-4. View

Schulz E, Bhui R, Love B, Brier B, Todd M, Gershman S . Structured, uncertainty-driven exploration in real-world consumer choice. Proc Natl Acad Sci U S A. 2019; 116(28):13903-13908. PMC: 6628813. DOI: 10.1073/pnas.1821028116. View

Kakade S, Dayan P . Dopamine: generalization and bonuses. Neural Netw. 2002; 15(4-6):549-59. DOI: 10.1016/s0893-6080(02)00048-5. View

Gershman S . Deconstructing the human algorithms for exploration. Cognition. 2018; 173:34-42. PMC: 5801139. DOI: 10.1016/j.cognition.2017.12.014. View

10.

Donkin C, Little D, Houpt J . Assessing the speed--accuracy trade-off effect on the capacity of information processing. J Exp Psychol Hum Percept Perform. 2014; 40(3):1183-202. DOI: 10.1037/a0035947. View

11.

Drugowitsch J, DeAngelis G, Angelaki D, Pouget A . Tuning the speed-accuracy trade-off to maximize reward rate in multisensory decision-making. Elife. 2015; 4:e06678. PMC: 4487075. DOI: 10.7554/eLife.06678. View

12.

Olschewski S, Rieskamp J, Scheibehenne B . Taxing cognitive capacities reduces choice consistency rather than preference: A model-based test. J Exp Psychol Gen. 2018; 147(4):462-484. DOI: 10.1037/xge0000403. View

13.

Hayden B, Platt M . Temporal discounting predicts risk sensitivity in rhesus macaques. Curr Biol. 2007; 17(1):49-53. PMC: 1868415. DOI: 10.1016/j.cub.2006.10.055. View

14.

Young D, Goodie A, Hall D, Wu E . Decision making under time pressure, modeled in a prospect theory framework. Organ Behav Hum Decis Process. 2012; 118(2):179-188. PMC: 3375992. DOI: 10.1016/j.obhdp.2012.03.005. View

15.

Rieskamp J, Otto P . SSL: a theory of how people learn to select strategies. J Exp Psychol Gen. 2006; 135(2):207-36. DOI: 10.1037/0096-3445.135.2.207. View

16.

Gershman S . Origin of perseveration in the trade-off between reward and complexity. Cognition. 2020; 204:104394. DOI: 10.1016/j.cognition.2020.104394. View

17.

Busemeyer J . Decision making under uncertainty: a comparison of simple scalability, fixed-sample, and sequential-sampling models. J Exp Psychol Learn Mem Cogn. 1985; 11(3):538-64. DOI: 10.1037//0278-7393.11.3.538. View

18.

Miller J . Information input overload and psychopathology. Am J Psychiatry. 1960; 116:695-704. DOI: 10.1176/ajp.116.8.695. View

19.

Dasgupta I, Schulz E, Gershman S . Where do hypotheses come from?. Cogn Psychol. 2017; 96:1-25. DOI: 10.1016/j.cogpsych.2017.05.001. View

20.

Miller K, Shenhav A, Ludvig E . Habits without values. Psychol Rev. 2019; 126(2):292-311. PMC: 6548181. DOI: 10.1037/rev0000120. View