Publikation: Autonomy promotes the evolution of cooperation in prisoner's dilemma
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Population structure has been widely reported to foster cooperation in spatially structured populations, where individuals interact with all of their network neighbors defined by the spatial structure in each generation. However, most results rely on the assumption that individuals strictly interact with all of their neighbors during evolution. In reality, human beings, with sophisticated psychology, are willing to interact with some of their neighbors from time to time. Thus, individuals may not play games with all neighbors due to their psychological factors. Here we investigate how the autonomy, one of the basic psychological needs, affects the fate of cooperators in various social networks. By constructing a dynamical effective network, we find that the introduction of autonomy favors cooperative behavior. Further systematical studies by eliminating heterogeneity and the dynamic characteristics of the network reveal that autonomy plays a pivotal role in the evolution of cooperation. Moreover, we find that a moderate effective network degree, defined by the product of the original network degree and the level of autonomy, maximizes the cooperation on networks connecting individuals with fixed neighbors. Our results offer a possible way for organizations to improve individuals' cooperation and shed light on the importance of individuals' psychology on the evolution of cooperation.
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LI, Liang, Chen CHEN, Aming LI, 2020. Autonomy promotes the evolution of cooperation in prisoner's dilemma. In: Physical Review E. American Physical Society (APS). 2020, 102(4), 042402. ISSN 2470-0045. eISSN 2470-0053. Available under: doi: 10.1103/PhysRevE.102.042402BibTex
@article{Li2020-10-06Auton-51623, year={2020}, doi={10.1103/PhysRevE.102.042402}, title={Autonomy promotes the evolution of cooperation in prisoner's dilemma}, number={4}, volume={102}, issn={2470-0045}, journal={Physical Review E}, author={Li, Liang and Chen, Chen and Li, Aming}, note={Article Number: 042402} }
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