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.
Highlights
Received: June 13, 2017Accepted: November 21, 2017Published: December 8, 2017
Rand et al have shown that humans present network reciprocity if the benefit-to-cost ratio, a main parameter of the prisoner’s dilemma game (PDG), is larger than the degree of nodes in the network [21], which is consistent with the prediction of evolutionary game theory [8]
We have numerically shown that an aspiration-based reinforcement learning model, the BM model, produces network reciprocity if and only if the benefit-to-cost ratio in the donation game is large relative to the node’s degree
Summary
Received: June 13, 2017Accepted: November 21, 2017Published: December 8, 2017. A series of laboratory experiments using human participants involved in the prisoner’s dilemma game (PDG) has produced results that are not necessarily consistent with spatial and network reciprocity. Rand et al have shown that humans present network reciprocity if the benefit-to-cost ratio, a main parameter of the PDG, is larger than the degree of nodes in the network (i.e., number of neighbors per player) [21], which is consistent with the prediction of evolutionary game theory [8].
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