Partner Selection for the Emergence of Cooperation in Multi-Agent Systems Using Reinforcement Learning

Understand

Social dilemmas have been widely studied to explain how humans are able to cooperate in society.

• Considerable effort has been invested in designing artificial agents for social dilemmas that incorporate explicit agent motivations that are chosen to favor coordinated or cooperative responses.
• The prevalence of this general approach points towards the importance of achieving an understanding of both an agent's internal design and external environment dynamics that facilitate cooperative behavior.
• In this paper, we investigate how partner selection can promote cooperative behavior between agents who are trained to maximize a purely selfish objective function.