Deterministic and stochastic cooperation transitions in evolutionary games on networks.
Nagi Khalil1, I Leyva1,2, J A Almendral1,2
1Complex Systems Group & GISC, Universidad Rey Juan Carlos, Móstoles, 28933 Madrid, Spain.
Physical Review. E
|June 17, 2023
Summary
Network reciprocity drives cooperation transitions in evolutionary social dilemmas. Optimal social temperatures can maximize or minimize cooperation frequency, revealing critical behaviors in structured populations.
Area of Science:
- Evolutionary game theory
- Complex systems analysis
- Network science
Background:
- Cooperative dynamics in networks are well-studied but transitions driven by network reciprocity remain unclear.
- Understanding critical behaviors in evolutionary social dilemmas on structured populations is essential.
Purpose of the Study:
- Investigate critical behaviors of evolutionary social dilemmas on structured populations.
- Analyze the conditions and mechanisms driving cooperation transitions via network reciprocity.
Main Methods:
- Utilized master equations and Monte Carlo simulations for theoretical and empirical analysis.
- Developed a framework to describe absorbing, quasi-absorbing, and mixed strategy states.
- Examined transition nature (continuous or discontinuous) as system parameters change.
Main Results:
- Identified discontinuous copying probabilities under deterministic decision-making, leading to abrupt state changes.
- Revealed continuous and discontinuous phase transitions in large systems with increasing temperature.
- Discovered optimal 'social temperatures' that either maximize or minimize cooperation frequency.
Conclusions:
- Network reciprocity can induce abrupt cooperation transitions, especially in deterministic scenarios.
- System temperature plays a crucial role in phase transitions, with identifiable optimal points for cooperation.
- The study provides a comprehensive framework for understanding cooperation dynamics in structured populations.
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