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Updated: May 24, 2025

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
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Dynamic evolution in multi-player networked trust games with graded punishment.

Juan Wang1,2, Zhuo Liu1,2, Yan Xu3

  • 1Tianjin Key Laboratory for Control Theory and Complicated Industry Systems, Tianjin University of Technology, Tianjin 300384, China.

Chaos (Woodbury, N.Y.)
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Summary

A graded punishment strategy effectively reduces untrustworthy behavior in networked trust games. Balancing penalty costs and amounts is key to sustaining and improving trust levels in society.

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Area of Science:

  • Behavioral Economics
  • Network Science
  • Game Theory

Background:

  • Trust is fundamental to societal function.
  • Sustaining trust among self-interested individuals is challenging.
  • Networked trust games model social interactions.

Purpose of the Study:

  • To investigate the impact of graded punishment on trust.
  • To observe trust dynamics in a networked N-player trust game.
  • To identify conditions for effective trust enhancement.

Main Methods:

  • Incorporation of a graded punishment strategy into a networked N-player trust game.
  • Utilizing Monte Carlo simulations to analyze behavior progression.
  • Examining the role of punishers in excluding untrustworthy actors.

Main Results:

  • Graded punishment significantly curtails untrustworthy conduct.
  • The strategy has the potential to eliminate untrustworthy behavior.
  • Overall trust levels within the population improve.

Conclusions:

  • Graded punishment is an effective tool for fostering trust.
  • Balancing penalty cost and amount is critical for system stability.
  • The study offers insights for enhancing trust in networked societies.