Sharing is not erring: Pseudo-reciprocity in collective search
Imen Bouhlel, Charley M. WuiD, Nobuyuki Hanaki, Robert L. Goldstone
Abstract
Information sharing in competitive environments may seem counterintuitive, yet it is widely observed in humans and other animals. For instance, the open-source software movement has led to new and valuable technologies being released publicly to facilitate broader collaboration and further innovation. What drives this behavior and under which conditions can it be beneficial for an individual? Using simulations in both static and dynamic environments, we show that sharing information can lead to individual benefits through the mechanisms of pseudo-reciprocity, whereby shared information leads to by-product benefits for an individual without the need for explicit reciprocation. Crucially, imitation with a certain level of innovation is required to avoid a tragedy of the commons, while the mechanism of a local visibility radius allows for the coordination of self-organizing collectives of agents. When these two mechanisms are present, we find robust evidence for the benefits of sharing--even when others do not reciprocate.
02 /Specification & Classification
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