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Probabilistic Cue Combination: Less is More

Identifieur interne : 001B42 ( Pmc/Curation ); précédent : 001B41; suivant : 001B43

Probabilistic Cue Combination: Less is More

Auteurs : Daniel Yurovsky ; Ty W. Boyer ; Linda B. Smith ; Chen Yu

Source :

RBID : PMC:3582171

Abstract

Learning about the structure of the world requires learning probabilistic relationships: rules in which cues do not predict outcomes with certainty. However, in some cases, the ability to track probabilistic relationships is a handicap, leading adults to perform non-normatively in prediction tasks. For example, in the dilution effect, predictions made from the combination of two cues of different strengths are less accurate than those made from the stronger cue alone. Here we show that dilution is an adult problem; 11-month-old infants combine strong and weak predictors normatively. These results extend and add support for the less is more hypothesis: limited cognitive resources can lead children to represent probabilistic information differently from adults, and this difference in representation can have important downstream consequences for prediction.


Url:
DOI: 10.1111/desc.12011
PubMed: 23432826
PubMed Central: 3582171

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PMC:3582171

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Daniel Yurovsky
<affiliation>
<nlm:aff id="A1">Department of Psychology, Stanford University</nlm:aff>
<wicri:noCountry code="subfield">Stanford University</wicri:noCountry>
</affiliation>
Ty W. Boyer
<affiliation>
<nlm:aff id="A2">Department of Psychology, Georgia Southern University</nlm:aff>
<wicri:noCountry code="subfield">Georgia Southern University</wicri:noCountry>
</affiliation>
Linda B. Smith
<affiliation>
<nlm:aff id="A3">Department of Psychological and Brain Sciences and Program in Cognitive Science, Indiana University</nlm:aff>
<wicri:noCountry code="subfield">Indiana University</wicri:noCountry>
</affiliation>
Chen Yu
<affiliation>
<nlm:aff id="A3">Department of Psychological and Brain Sciences and Program in Cognitive Science, Indiana University</nlm:aff>
<wicri:noCountry code="subfield">Indiana University</wicri:noCountry>
</affiliation>

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<p id="P1">Learning about the structure of the world requires learning probabilistic relationships: rules in which cues do not predict outcomes with certainty. However, in some cases, the ability to track probabilistic relationships is a handicap, leading adults to perform non-normatively in prediction tasks. For example, in the
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, predictions made from the combination of two cues of different strengths are less accurate than those made from the stronger cue alone. Here we show that
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is an adult problem; 11-month-old infants combine strong and weak predictors normatively. These results extend and add support for the
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hypothesis: limited cognitive resources can lead children to represent probabilistic information differently from adults, and this difference in representation can have important downstream consequences for prediction.</p>
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Department of Psychology, Stanford University</aff>
<aff id="A2">
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Department of Psychology, Georgia Southern University</aff>
<aff id="A3">
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Department of Psychological and Brain Sciences and Program in Cognitive Science, Indiana University</aff>
<author-notes>
<corresp id="FN1">Address correspondence to: Daniel Yurovsky, Department of Psychology, Jordan Hall, Building 01-420, Stanford University, 450 Serra Mall, Stanford, CA, 94305,
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, Phone: 812-856-1920</corresp>
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<day>01</day>
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<year>2014</year>
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<volume>16</volume>
<issue>2</issue>
<fpage>149</fpage>
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<abstract>
<p id="P1">Learning about the structure of the world requires learning probabilistic relationships: rules in which cues do not predict outcomes with certainty. However, in some cases, the ability to track probabilistic relationships is a handicap, leading adults to perform non-normatively in prediction tasks. For example, in the
<italic>dilution effect</italic>
, predictions made from the combination of two cues of different strengths are less accurate than those made from the stronger cue alone. Here we show that
<italic>dilution</italic>
is an adult problem; 11-month-old infants combine strong and weak predictors normatively. These results extend and add support for the
<italic>less is more</italic>
hypothesis: limited cognitive resources can lead children to represent probabilistic information differently from adults, and this difference in representation can have important downstream consequences for prediction.</p>
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<kwd-group>
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