Literature DB >> 12749466

Is probability matching smart? Associations between probabilistic choices and cognitive ability.

Keith E Stanovich1.   

Abstract

In three experiments involving over 1,500 university students (n = 1,557) and two different probabilistic choice tasks, we found that the utility-maximizing strategy of choosing the most probable alternative was not the majority response. In a story problem version of a probabilistic choice task in which participants chose from among five different strategies,the maximizing response and the probability-matching response were each selected by a similar number of students (roughly 35% of the sample selected each). In a more continuous, or trial-by-trial, task, the utility-maximizing response was chosen by only one half as many students asthe probability-matching response. More important, in both versions of the task, the participants preferring the utility-maximizing response were significantly higher in cognitive ability than were the participants showing a probability-matching tendency. Critiques of the traditional interpretation of probability matching as nonoptimal may well help explain why some humans are drawn to the nonmaximizing behavior of probability matching, but the traditional heuristics and biases interpretation can most easily accommodate the finding that participants high in computational ability are more likely to carry out the rule-based cognitive procedures that lead to maximizing behavior.

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Year:  2003        PMID: 12749466     DOI: 10.3758/bf03194383

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


  15 in total

1.  Working memory, short-term memory, and general fluid intelligence: a latent-variable approach.

Authors:  Randall W Engle; Stephen W Tuholski; James E Laughlin; Andrew R A Conway
Journal:  J Exp Psychol Gen       Date:  1999-09

2.  Individual differences in reasoning: implications for the rationality debate?

Authors:  K E Stanovich; R F West
Journal:  Behav Brain Sci       Date:  2000-10       Impact factor: 12.579

3.  Précis of Simple heuristics that make us smart.

Authors:  P M Todd; G Gigerenzer
Journal:  Behav Brain Sci       Date:  2000-10       Impact factor: 12.579

4.  Probability matching: encouraging optimal responding in humans.

Authors:  Edmund Fantino; Ali Esfandiari
Journal:  Can J Exp Psychol       Date:  2002-03

5.  SEQUENTIAL PATTERNS AND MAXIMIZING.

Authors:  C R PETERSON; Z J ULEHLA
Journal:  J Exp Psychol       Date:  1965-01

Review 6.  Rationality.

Authors:  Eldar Shafir; Robyn A LeBoeuf
Journal:  Annu Rev Psychol       Date:  2002       Impact factor: 24.137

7.  The probabilistic approach to human reasoning.

Authors:  M Oaksford; N Chater
Journal:  Trends Cogn Sci       Date:  2001-08-01       Impact factor: 20.229

Review 8.  Beyond intuition and instinct blindness: toward an evolutionarily rigorous cognitive science.

Authors:  L Cosmides; J Tooby
Journal:  Cognition       Date:  1994 Apr-Jun

9.  Adaptive "coin-flipping": a decision-theoretic examination of natural selection for random individual variation.

Authors:  W S Cooper; R H Kaplan
Journal:  J Theor Biol       Date:  1982-01-07       Impact factor: 2.691

10.  When and why do people avoid unknown probabilities in decisions under uncertainty? Testing some predictions from optimal foraging theory.

Authors:  C Rode; L Cosmides; W Hell; J Tooby
Journal:  Cognition       Date:  1999-10-26
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  25 in total

1.  Probability matching and strategy availability.

Authors:  Derek J Koehler; Greta James
Journal:  Mem Cognit       Date:  2010-09

2.  More heads choose better than one: Group decision making can eliminate probability matching.

Authors:  Christin Schulze; Ben R Newell
Journal:  Psychon Bull Rev       Date:  2016-06

3.  Self-reported strategies in decisions under risk: role of feedback, reasoning abilities, executive functions, short-term-memory, and working memory.

Authors:  Johannes Schiebener; Matthias Brand
Journal:  Cogn Process       Date:  2015-08-20

4.  Taking the easy way out? Increasing implementation effort reduces probability maximizing under cognitive load.

Authors:  Christin Schulze; Ben R Newell
Journal:  Mem Cognit       Date:  2016-07

5.  The Cognitive Reflection Test as a predictor of performance on heuristics-and-biases tasks.

Authors:  Maggie E Toplak; Richard F West; Keith E Stanovich
Journal:  Mem Cognit       Date:  2011-10

Review 6.  Decision Making Under Objective Risk Conditions-a Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences.

Authors:  Johannes Schiebener; Matthias Brand
Journal:  Neuropsychol Rev       Date:  2015-04-18       Impact factor: 7.444

7.  Betting on Illusory Patterns: Probability Matching in Habitual Gamblers.

Authors:  Wolfgang Gaissmaier; Andreas Wilke; Benjamin Scheibehenne; Paige McCanney; H Clark Barrett
Journal:  J Gambl Stud       Date:  2016-03

Review 8.  Reinforcement learning improves behaviour from evaluative feedback.

Authors:  Michael L Littman
Journal:  Nature       Date:  2015-05-28       Impact factor: 49.962

9.  Probability matching as a computational strategy used in perception.

Authors:  David R Wozny; Ulrik R Beierholm; Ladan Shams
Journal:  PLoS Comput Biol       Date:  2010-08-05       Impact factor: 4.475

Review 10.  Good judgments do not require complex cognition.

Authors:  Julian N Marewski; Wolfgang Gaissmaier; Gerd Gigerenzer
Journal:  Cogn Process       Date:  2009-09-27
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