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Decision Making01:20

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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Related Experiment Video

Updated: Jun 26, 2026

Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking
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Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking

Published on: December 16, 2010

Game theory of mind.

Wako Yoshida1, Ray J Dolan, Karl J Friston

  • 1The Wellcome Trust Centre for Neuroimaging, University College London, UK. w.yoshida@fil.ion.ucl.ac.uk

Plos Computational Biology
|December 30, 2008
PubMed
Summary

This study models "theory of mind" using game theory to understand how we predict others' intentions. Bounded recursion in strategic interactions allows inferring an opponent's sophistication from choices.

Area of Science:

  • Cognitive Science
  • Game Theory
  • Neuroscience

Background:

  • Understanding how individuals represent and predict others' intentions is crucial for social interaction.
  • Existing models often assume infinite recursion in strategic thinking, which is unrealistic.

Purpose of the Study:

  • To introduce a computational model of 'theory of mind' based on game theory and optimal control.
  • To investigate how bounded recursion in strategic reasoning affects the inference of an opponent's sophistication.

Main Methods:

  • Developed a 'game theory of mind' model using recursive value function optimization.
  • Introduced the concept of bounded recursion and the need to infer opponent sophistication.
  • Utilized model comparison with generative models to analyze choices in sequential games, including the 'stag-hunt' game.

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The HoneyComb Paradigm for Research on Collective Human Behavior
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The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

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Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking
13:40

Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking

Published on: December 16, 2010

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Main Results:

  • Demonstrated that inferring an opponent's sophistication is possible by analyzing choices in sequential games.
  • Showed that bounded recursion necessitates estimating the opponent's level of strategic thinking.
  • Identified that prosocial utility optimization can mimic sophisticated behavior without actual inference.

Conclusions:

  • The model provides a framework for quantifying strategic sophistication in social interactions.
  • Bounded recursion in theory of mind is a key factor in predicting behavior in games.
  • Prosocial utility offers an alternative explanation for seemingly altruistic behavior in game theory contexts.