Special agents can promote cooperation in the population

Area of Science:

• Evolutionary game theory
• Agent-based modeling
• Collective behavior

Background:

• Cooperation is essential but challenging among self-interested agents without central control.
• Hostile environments often hinder cooperation.
• Existing mechanisms struggle to promote cooperation without altering fundamental rules.

Purpose of the Study:

• To investigate mechanisms promoting cooperation in self-interested agent groups.
• To introduce and evaluate a novel "soft control" mechanism.
• To test the robustness and applicability of soft control in various scenarios.

Main Methods:

• Numerical experiments on the finite, end-unknown Repeated Prisoner's Dilemma (RPD).
• Introduction of special agents employing unique strategies and knowledge sharing.
• Analysis of soft control's effectiveness under diverse settings and noise.

Main Results:

• Complete population interaction is detrimental to cooperation in RPD.
• Soft control significantly promotes cooperation.
• The mechanism demonstrates robustness to noise and applicability in other scenarios.

Conclusions:

• Soft control is an effective mechanism for promoting cooperation in self-interested populations.
• This approach offers a novel direction for studying reciprocal behaviors and collective action.
• The findings are validated through simulations and analytical proof.