Evolution of cooperative imitators in social networks

Area of Science:

• Evolutionary Game Theory
• Network Reciprocity
• Agent-Based Modeling

Background:

• Imitation dynamics are common in evolutionary game models for network reciprocity.
• The prevalence of semirational imitators in these models remains underexplored.

Purpose of the Study:

• Investigate the coevolutionary dynamics of cooperation and partnership adjustment.
• Model a population comprising semirational imitators and rational payoff maximizers.

Main Methods:

• Individual-based simulations of a polygenic population.
• Modeling rational agents as best responders and semirational agents using imitation and reputation rules.
• Analyzing partnership adjustment and strategy updating mechanisms.

Main Results:

• Cooperation fails to evolve in a population of only best responders, even with partner switching.
• A stable community of cooperative imitators emerges when semirational imitators are present.
• Birth-death selection can eliminate best responders, establishing a cooperative imitator regime.
• Cooperative imitators are evolutionarily favored on dynamic networks compared to fixed ones.

Conclusions:

• Semirational imitators are crucial for the evolution of cooperation in network reciprocity models.
• Dynamic partnership adjustment and imitation dynamics create a favorable environment for cooperative strategies.
• Agent-based modeling provides insights into complex social dynamics and evolutionary stability.