Reinforcement learning account of network reciprocity

Takahiro Ezaki and Naoki Masuda

PLOS ONE, 2017, vol. 12, issue 12, 1-8

Abstract: Evolutionary game theory predicts that cooperation in social dilemma games is promoted when agents are connected as a network. However, when networks are fixed over time, humans do not necessarily show enhanced mutual cooperation. Here we show that reinforcement learning (specifically, the so-called Bush-Mosteller model) approximately explains the experimentally observed network reciprocity and the lack thereof in a parameter region spanned by the benefit-to-cost ratio and the node’s degree. Thus, we significantly extend previously obtained numerical results.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0189220

DOI: 10.1371/journal.pone.0189220

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