You don't want to know what you're missing

When people learn to make decisions from experience, a reasonable intuition is that additional relevant information should improve their performance. In contrast, we find that additional information about foregone rewards (i.e., what could have gained at each point by making a different choice) seve...

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Main Authors: A. Ross Otto, Bradley C. Love
Format: Article
Language:English
Published: Cambridge University Press 2010-02-01
Series:Judgment and Decision Making
Subjects:
Online Access:http://journal.sjdm.org/10/9923/jdm9923.pdf
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author A. Ross Otto
Bradley C. Love
author_facet A. Ross Otto
Bradley C. Love
author_sort A. Ross Otto
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description When people learn to make decisions from experience, a reasonable intuition is that additional relevant information should improve their performance. In contrast, we find that additional information about foregone rewards (i.e., what could have gained at each point by making a different choice) severely hinders participants' ability to repeatedly make choices that maximize long-term gains. We conclude that foregone reward information accentuates the local superiority of short-term options (e.g., consumption) and consequently biases choice away from productive long-term options (e.g., exercise). These conclusions are consistent with a standard reinforcement-learning mechanism that processes information about experienced and forgone rewards. In contrast to related contributions using delay-of-gratification paradigms, we do not posit separate top-down and emotion-driven systems to explain performance. We find that individual and group data are well characterized by a single reinforcement-learning mechanism that combines information about experienced and foregone rewards.
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spelling doaj.art-eded103f17474afe91f3cf15b7f4608e2023-09-02T10:39:41ZengCambridge University PressJudgment and Decision Making1930-29752010-02-0151110You don't want to know what you're missingA. Ross OttoBradley C. LoveWhen people learn to make decisions from experience, a reasonable intuition is that additional relevant information should improve their performance. In contrast, we find that additional information about foregone rewards (i.e., what could have gained at each point by making a different choice) severely hinders participants' ability to repeatedly make choices that maximize long-term gains. We conclude that foregone reward information accentuates the local superiority of short-term options (e.g., consumption) and consequently biases choice away from productive long-term options (e.g., exercise). These conclusions are consistent with a standard reinforcement-learning mechanism that processes information about experienced and forgone rewards. In contrast to related contributions using delay-of-gratification paradigms, we do not posit separate top-down and emotion-driven systems to explain performance. We find that individual and group data are well characterized by a single reinforcement-learning mechanism that combines information about experienced and foregone rewards.http://journal.sjdm.org/10/9923/jdm9923.pdfdecision-makingdelay of gratificationlearningself-controldynamic environmentsreinforcement learning.
spellingShingle A. Ross Otto
Bradley C. Love
You don't want to know what you're missing
Judgment and Decision Making
decision-making
delay of gratification
learning
self-control
dynamic environments
reinforcement learning.
title You don't want to know what you're missing
title_full You don't want to know what you're missing
title_fullStr You don't want to know what you're missing
title_full_unstemmed You don't want to know what you're missing
title_short You don't want to know what you're missing
title_sort you don t want to know what you re missing
topic decision-making
delay of gratification
learning
self-control
dynamic environments
reinforcement learning.
url http://journal.sjdm.org/10/9923/jdm9923.pdf
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