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The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
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Concurrent performance in a three-alternative choice situation: response allocation in a Rock/Paper/Scissors game.

Brian D Kangas1, Meredith S Berry, Rachel N Cassidy

  • 1University of Florida, Gainesville, FL 32611-2250, United States. kangas@ufl.edu

Behavioural Processes
|June 27, 2009
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Summary

Human subjects playing Rock/Paper/Scissors against a computer demonstrated undermatching to programmed probabilities. Providing probability information led to counter-response strategies and improved reinforcement rates, validating the generalized matching law.

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Area of Science:

  • Behavioral psychology
  • Decision-making research
  • Reinforcement learning

Background:

  • Human choice behavior is complex and influenced by probabilistic outcomes.
  • The generalized matching law (GML) is a theoretical framework for understanding choice behavior.
  • Laboratory simulations offer controlled environments to study decision-making.

Purpose of the Study:

  • To investigate human response allocation in a simulated game against a probabilistic computer opponent.
  • To test the applicability of the generalized matching law to complex human choice.
  • To examine the impact of explicit probability information on strategic responding.

Main Methods:

  • Adult participants played a simulated Rock/Paper/Scissors game across multiple trials.
  • Computer opponent responses were governed by programmed, varying probabilities.
  • Experiment 1 involved no explicit probability information; Experiment 2 provided this information.

Main Results:

  • Undermatching to programmed probabilities was observed in Experiment 1.
  • In Experiment 2, participants largely adopted counter-strategies to the computer's dominant response.
  • Providing probability information led to minor overmatching and increased reinforcement rates.

Conclusions:

  • The generalized matching law effectively describes complex human choice in a gaming context.
  • Laboratory methods can capture essential features of real-world human decision-making.
  • Strategic adjustments in response to probabilistic feedback significantly impact reinforcement outcomes.