摘要：SummaryCooperation in human groups is challenging, and various mechanisms are required to sustain it, although it nevertheless usually decays over time. Here, we perform theoretically informed experiments involving networks of humans (1,024 subjects in 64 networks) playing a public-goods game to which we sometimes added autonomous agents (bots) programmed to use only local knowledge. We show that cooperation can not only be stabilized, but even promoted, when the bots intervene in the partner selections made by the humans, re-shaping social connections locally within a larger group. Cooperation rates increased from 60.4% at baseline to 79.4% at the end. This network-intervention strategy outperformed other strategies, such as adding bots playing tit-for-tat. We also confirm that even a single bot can foster cooperation in human groups by using a mixed strategy designed to support the development of cooperative clusters. Simple artificial intelligence can increase the cooperation of groups.Graphical AbstractDisplay OmittedHighlights•Network experiments show that adding bots can promote cooperation in human groups•To promote cooperation, bots intervene locally in the connections between humans•Even a single bot, with simple AI, can foster cooperation by network engineering•Network-engineering bots are effective even when identified as botsBehavioral Neuroscience; Cognitive Neuroscience; Human-Computer Interaction; Collaborative Computing
