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Published on: September 28, 2018
The rationality of prejudices
Thomas Chadefaux1, Dirk Helbing
1Swiss Federal Institute of Technology Zurich, Zurich, Switzerland. thomas.chadefaux@gess.ethz.ch
Plos One
|February 24, 2012
Summary
Prejudiced strategies in the repeated prisoner's dilemma learn quickly by using player traits to infer behavior. These strategies outperform standard approaches like Tit-For-Tat in rapidly changing populations.
Area of Science:
- Game Theory
- Behavioral Economics
- Computational Social Science
Background:
- The repeated prisoner's dilemma is a fundamental model for studying cooperation and defection.
- Player behavior in social dilemmas can be influenced by observable characteristics.
- Standard strategies like Tit-For-Tat assume no prior information about opponents.
Purpose of the Study:
- To analyze the performance of
- prejudiced
- strategies in an N-player repeated prisoner's dilemma.
Main Methods:
- Modeling an N-player repeated prisoner's dilemma with player traits influencing behavior.
- Defining prejudiced strategies that infer behavior from observed traits.
- Comparing the performance of prejudiced strategies against Tit-For-Tat and ALLD.
Main Results:
- Prejudiced strategies demonstrated rapid learning capabilities.
- These strategies showed superior performance in environments with high population turnover.
- Prejudiced strategies systematically outperformed Tit-For-Tat and ALLD under rapid environmental changes.
Conclusions:
- Prejudiced strategies offer an adaptive advantage in dynamic social environments.
- Trait-based inference can lead to efficient behavioral adaptation in repeated games.
- The findings suggest that incorporating observable traits can enhance evolutionary game theory models.
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