Adaptive willingness resolves social dilemma in network populations.

Clicks: 346
ID: 69690
2019
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Abstract
Cooperation is an effective manner to enable different elements of complex networks to work well. In this work, we propose a coevolution mechanism of learning willingness in the network population: an agent will be more likely to imitate a given neighbor's strategy if her payoff is not less than the average performance of all her neighbors. Interestingly, increase of learning willingness will greatly promote cooperation even under the environment of extremely beneficial temptation to defectors. Through a microscopic analysis, it is unveiled that cooperators are protected due to the appearance of large-size clusters. Pair approximation theory also validates all these findings. Such an adaptive mechanism thus provides a feasible solution to relieve social dilemmas and will inspire further studies.
Reference Key
zhu2019adaptivechaos Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zhu, Peican;Song, Zhao;Guo, Hao;Wang, Zhen;Zhao, Tianyun;
Journal chaos (woodbury, ny)
Year 2019
DOI
10.1063/1.5093046
URL
Keywords
gaba disinhibition computational modeling brain connectivity tms-eeg disorders of consciousness (doc) feedforward inhibition

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