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Computation noise in human learning and decision-making: origin, impact, function
7 references·16 citing·50 second hop
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(1990)Self-Confidence and Personal Motivation (2002)Choosing between Causal Interpretations: An Experimental Study (2024)Political ideology, emotion response, and confirmation bias (2024)Motivated Procrastination (2026)Stock Market Overreactions to Bad News in Good Times: A Rational Expectations Equilibrium Model (1999)Expectations of Returns and Expected Returns (2014)Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts (2015)What Makes Teams Work: Group Effectiveness Research from the Shop Floor to the Executive Suite (1997)G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences (2007)Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err (2014)
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References

  • 2019Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources892 cited
  • 2018Efficient coding of subjective value200 cited
  • 2016Computational Precision of Mental Inference as Critical Source of Human Choice Suboptimality181 cited
  • 2016Economic irrationality is optimal during noisy decision making133 cited
  • 2016Choice variability and suboptimality in uncertain environments109 cited
  • 2018Decision by sampling implements efficient coding of psychoeconomic functions.98 cited
  • 2018A bias–variance trade-off governs individual differences in on-line learning in an unpredictable environment79 cited

Cited by

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  • 2024Insensitive Investors29 cited
  • 2023The autocorrelated Bayesian sampler: A rational process for probability judgments, estimates, confidence intervals, choices, confidence judgments, and response times.22 cited
  • 2024Dynamic noise estimation: A generalized method for modeling noise fluctuations in decision-making21 cited
  • 2023Adaptive tuning of human learning and choice variability to unexpected uncertainty20 cited
  • 2022Efficient stabilization of imprecise statistical inference through conditional belief updating

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17 cited
  • 2024Using recurrent neural network to estimate irreducible stochasticity in human choice behavior11 cited
  • 2023A unified explanation of variability and bias in human probability judgments: How computational noise explains the mean–variance signature.11 cited
  • 2022The effects of base rate neglect on sequential belief updating and real-world beliefs10 cited
  • 2024How do people predict a random walk? Lessons for models of human cognition.7 cited
  • 2022Current and expected affective valence interact to predict choice in recurrent decisions4 cited
  • 2024Using recurrent neural network to estimate irreducible stochasticity in human choice behavior4 cited
  • 2022Over- and Underweighting of Extreme Values in Decisions from Sequential Samples4 cited
  • 2024Multiple and subject-specific roles of uncertainty in reward-guided decision-making3 cited
  • 2025Enriching Psychological Research by Exploring the Source and Nature of Noise2 cited