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Social Exchange Theory02:06

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We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
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Related Experiment Video

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A Task for Assessing the Impact of a Partner on the Speed and Accuracy of Motor Performance in Rats
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Published on: October 17, 2019

Cooperation prevails when individuals adjust their social ties.

Francisco C Santos1, Jorge M Pacheco, Tom Lenaerts

  • 1Computer and Decision Engineering Department, Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle, Université Libre de Bruxelles, Brussels, Belgium.

Plos Computational Biology
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Summary

Cooperation thrives when individuals self-organize their strategies and social ties, leading to evolutionary success for cooperators. This topological co-evolution is crucial for sustaining cooperation in complex social networks.

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Area of Science:

  • Evolutionary Game Theory
  • Network Science
  • Computational Biology

Background:

  • Conventional evolutionary game theory struggles to explain the prevalence of cooperation, as it often favors selfish strategies.
  • Cooperation is limited by network structure, particularly in low-connectivity environments.
  • Real-world networks display high average connectivity and significant heterogeneity, posing a challenge to existing models.

Purpose of the Study:

  • To investigate the role of self-organization in the evolution of cooperation within social networks.
  • To explore how the co-evolution of individual strategy and network structure impacts cooperation.
  • To reconcile theoretical predictions with empirical observations of cooperation in heterogeneous networks.

Main Methods:

  • Development of a computational model where individuals self-organize both strategy and social ties based on self-interest.
  • Analysis of the interplay between strategy evolution time scales and network structure evolution time scales (ratio W).
  • Simulation of evolutionary dynamics on emergent, self-organized networks.

Main Results:

  • The entangled evolution of strategy and network structure is a key mechanism for sustaining cooperation.
  • A critical ratio (W) exists, above which cooperators outperform defectors.
  • Emergent networks exhibit realistic heterogeneity, with maximal heterogeneity at the critical W value.

Conclusions:

  • Self-organization of social ties, coupled with strategy evolution, can generate realistic heterogeneous networks that support cooperation.
  • Cooperation in high-connectivity, heterogeneous networks requires topological co-evolution, not just social viscosity.
  • This model provides a mechanism for the widespread prevalence of cooperation in diverse living systems.