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Evolutionary dynamics of group fairness.

Fernando P Santos1, Francisco C Santos1, Ana Paiva2

  • 1INESC-ID and Instituto Superior Técnico, Universidade de Lisboa, IST-Tagusparque, 2744-016 Porto Salvo, Portugal; ATP-group, Instituto de Investigação Interdisciplinar, P-1649-003 Lisboa Codex, Portugal.

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Summary
This summary is machine-generated.

This study introduces the Multiplayer Ultimatum Game to explore fairness in groups. Stricter consensus rules and stochastic errors promote fairer collective action and more tolerant players.

Keywords:
Behavioral dynamicsCollective actionCooperationEvolutionary game theoryUltimatum game

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Area of Science:

  • Behavioral Economics
  • Evolutionary Game Theory
  • Social Psychology

Background:

  • Fairness is extensively studied in two-person games like the Ultimatum Game.
  • Human collective action involves multiple individuals, where fairness dynamics differ significantly from two-person scenarios.
  • Existing models do not fully capture fairness in multi-individual settings.

Purpose of the Study:

  • To generalize the Ultimatum Game for an arbitrary number of players, termed the Multiplayer Ultimatum Game.
  • To investigate the evolutionary dynamics of fairness in populations using this new model.
  • To analyze how group consensus and stochastic effects influence fair collective action.

Main Methods:

  • Development of the Multiplayer Ultimatum Game model.
  • Application of evolutionary game theory for analytical insights.
  • Conducting numerical simulations to observe population dynamics.

Main Results:

  • Stringent consensus thresholds significantly increase proposal values, leading to fairer outcomes.
  • The Multiplayer Ultimatum Game fosters more tolerant players.
  • Stochastic effects, including imitation and assessment errors, can enhance the success of fair collective action.

Conclusions:

  • The Multiplayer Ultimatum Game provides a robust framework for studying fairness in group settings.
  • Group consensus mechanisms are crucial for achieving fairness and cooperation.
  • Randomness in decision-making or evaluation can paradoxically improve collective fairness.