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The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
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Limited trust in social network games.

Timothy Murray1, Jugal Garg1, Rakesh Nagi2

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Summary

Agents in social networks compete to become trustworthy partners, increasing overall utility. Competition drives this behavior, not altruism, though abundant opportunities can paradoxically decrease trustworthiness.

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Area of Science:

  • Social network analysis
  • Game theory
  • Agent-based modeling

Background:

  • Agents in social networks engage in collaborative activities to maximize individual utility.
  • Trustworthiness is a key factor in partner selection for mutually beneficial interactions.
  • Agents learn about and adapt to neighbors' trustworthiness through repeated interactions.

Purpose of the Study:

  • To model and analyze the emergence of trustworthy behavior in competitive social networks.
  • To investigate the impact of competition and learning on agent trustworthiness and utility.
  • To explore the relationship between partnership abundance and agent trustworthiness.

Main Methods:

  • Agent-based modeling of a social network where agents initiate and accept games (activities).
  • Incorporation of the game-theoretic concept of limited-trust to quantify trustworthiness.
  • Empirical trials on realistic social network structures to observe agent behavior evolution.

Main Results:

  • Agents are intrinsically motivated by competition to become trustworthy, enhancing overall utility.
  • Trustworthy behavior can increase net utility by up to 14.5%, with individual gains up to 25%.
  • Increased partnership opportunities paradoxically lead to decreased trustworthiness among agents.

Conclusions:

  • Competition, rather than altruism, is a primary driver for trustworthy behavior in social networks.
  • Trustworthiness significantly benefits individual and collective utility within a social network.
  • The dynamics of partner selection and learning influence the evolution of cooperative strategies.