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Cooperative behavior in human networks evolves dynamically. This study introduces a new algorithm showing cooperation strengthens relationships, while betrayal leads to loose, unstable networks reliant on new members.

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Area of Science:

  • Complex systems
  • Evolutionary game theory
  • Social network analysis

Background:

  • Human society exhibits diverse organizational networks.
  • Network structure and individual behavior vary widely.
  • This diversity is key for the emergence of cooperation.

Purpose of the Study:

  • To introduce a dynamic algorithm for individual network evolution.
  • To analyze the importance of different nodes in network evolution.
  • To describe the probabilities of cooperation and betrayal strategies.

Main Methods:

  • Dynamic algorithm for network evolution simulation.
  • Calculation of node importance during network evolution.
  • Simulation of cooperation and betrayal strategy dynamics.

Main Results:

  • Cooperative behavior promotes relationship evolution and better interpersonal networks.
  • Betrayal leads to loose interpersonal networks.
  • Betrayal networks require new nodes for continuity, creating "weak links".

Conclusions:

  • Cooperation fosters stable and evolving interpersonal networks.
  • Betrayal strategies result in fragile network structures.
  • Understanding network dynamics is crucial for social cooperation.