Promoting cooperation in the public goods game using artificial intelligent agents

Abstract The tragedy of the commons describes a dilemma where individually rational actions degrade shared resources. Strategies to overcome this issue remain limited. We examine how artificial intelligence (AI) agents can foster cooperation in Public Goods games, moving beyond traditional regulations. We test three scenarios: (1) Mandatory Cooperation Policy , requiring AI agents always to cooperate; (2) Player-Controlled Cooperation Policy , allowing players to control AI cooperation rates; and (3) Agents Mimic Players , where AI agents imitate human behaviors. Using computational evolutionary modeling, we show that only AI agents mimicking player behavior effectively reduce the synergy threshold needed for cooperation, resolving the dilemma. These findings suggest that designing AI agents to replicate human behaviors can enhance cooperation and improve collective welfare.