Of matchers and maximizers: How competition shapes choice under risk and uncertainty
•Probability matching or maximizing was reinforced in competitive choice tasks.•We observed accurate asymptotic adoption of both strategies.•Learning models based on competitor avoidance describe choice behavior best.•We demonstrated that probability matching can be optimal under competition. In a w...
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Published in | Cognitive psychology Vol. 78; pp. 78 - 98 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier Inc
01.05.2015
Academic Press |
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Abstract | •Probability matching or maximizing was reinforced in competitive choice tasks.•We observed accurate asymptotic adoption of both strategies.•Learning models based on competitor avoidance describe choice behavior best.•We demonstrated that probability matching can be optimal under competition.
In a world of limited resources, scarcity and rivalry are central challenges for decision makers—animals foraging for food, corporations seeking maximal profits, and athletes training to win, all strive against others competing for the same goals. In this article, we establish the role of competitive pressures for the facilitation of optimal decision making in simple sequential binary choice tasks. In two experiments, competition was introduced with a computerized opponent whose choice behavior reinforced one of two strategies: If the opponent probabilistically imitated participant choices, probability matching was optimal; if the opponent was indifferent, probability maximizing was optimal. We observed accurate asymptotic strategy use in both conditions irrespective of the provision of outcome probabilities, suggesting that participants were sensitive to the differences in opponent behavior. An analysis of reinforcement learning models established that computational conceptualizations of opponent behavior are critical to account for the observed divergence in strategy adoption. Our results provide a novel appraisal of probability matching and show how this individually ‘irrational’ choice phenomenon can be socially adaptive under competition. |
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AbstractList | In a world of limited resources, scarcity and rivalry are central challenges for decision makers-animals foraging for food, corporations seeking maximal profits, and athletes training to win, all strive against others competing for the same goals. In this article, we establish the role of competitive pressures for the facilitation of optimal decision making in simple sequential binary choice tasks. In two experiments, competition was introduced with a computerized opponent whose choice behavior reinforced one of two strategies: If the opponent probabilistically imitated participant choices, probability matching was optimal; if the opponent was indifferent, probability maximizing was optimal. We observed accurate asymptotic strategy use in both conditions irrespective of the provision of outcome probabilities, suggesting that participants were sensitive to the differences in opponent behavior. An analysis of reinforcement learning models established that computational conceptualizations of opponent behavior are critical to account for the observed divergence in strategy adoption. Our results provide a novel appraisal of probability matching and show how this individually 'irrational' choice phenomenon can be socially adaptive under competition. •Probability matching or maximizing was reinforced in competitive choice tasks.•We observed accurate asymptotic adoption of both strategies.•Learning models based on competitor avoidance describe choice behavior best.•We demonstrated that probability matching can be optimal under competition. In a world of limited resources, scarcity and rivalry are central challenges for decision makers—animals foraging for food, corporations seeking maximal profits, and athletes training to win, all strive against others competing for the same goals. In this article, we establish the role of competitive pressures for the facilitation of optimal decision making in simple sequential binary choice tasks. In two experiments, competition was introduced with a computerized opponent whose choice behavior reinforced one of two strategies: If the opponent probabilistically imitated participant choices, probability matching was optimal; if the opponent was indifferent, probability maximizing was optimal. We observed accurate asymptotic strategy use in both conditions irrespective of the provision of outcome probabilities, suggesting that participants were sensitive to the differences in opponent behavior. An analysis of reinforcement learning models established that computational conceptualizations of opponent behavior are critical to account for the observed divergence in strategy adoption. Our results provide a novel appraisal of probability matching and show how this individually ‘irrational’ choice phenomenon can be socially adaptive under competition. |
Author | Schulze, Christin Newell, Ben R. van Ravenzwaaij, Don |
Author_xml | – sequence: 1 givenname: Christin surname: Schulze fullname: Schulze, Christin email: cschulze@mpib-berlin.mpg.de organization: School of Psychology, University of New South Wales, Sydney, Australia – sequence: 2 givenname: Don surname: van Ravenzwaaij fullname: van Ravenzwaaij, Don organization: School of Psychology, University of New South Wales, Sydney, Australia – sequence: 3 givenname: Ben R. surname: Newell fullname: Newell, Ben R. organization: School of Psychology, University of New South Wales, Sydney, Australia |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25868112$$D View this record in MEDLINE/PubMed |
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Keywords | Competition Probability matching Cognitive models Decision making Reinforcement learning |
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Snippet | •Probability matching or maximizing was reinforced in competitive choice tasks.•We observed accurate asymptotic adoption of both strategies.•Learning models... In a world of limited resources, scarcity and rivalry are central challenges for decision makers-animals foraging for food, corporations seeking maximal... |
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SubjectTerms | Adolescent Asymptotic methods Choice Behavior Cognitive models Cognitive psychology Competition Competitive Behavior Decision Making Decision making models Female Humans Male Probability Probability matching Reinforcement (Psychology) Reinforcement learning Risk Uncertainty Young Adult |
Title | Of matchers and maximizers: How competition shapes choice under risk and uncertainty |
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