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author:

Fu, M.-J. (Fu, M.-J..) [1] | Yang, H.-X. (Yang, H.-X..) [2]

Indexed by:

Scopus

Abstract:

In this paper, we propose a stochastic win-stay-lose-learn in which an individual is more likely to imitate one of its nearest neighbor's strategy if its aspiration is not achieved. The results on the spatial public good game show that the cooperation can be greatly enhanced when the aspiration is moderate. Besides, we have studied the time evolution of the spatial distribution of strategies and the probability that cooperators and defectors choose to learn respectively. © 2018 World Scientific Publishing Company.

Keyword:

cooperation; Spatial public goods game; win-stay-lose-learn

Community:

  • [ 1 ] [Fu, M.-J.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Fu, M.-J.]Key Laboratory of Intelligent Metro of Universities in Fujian, Fuzhou University, Fuzhou, 350116, China
  • [ 3 ] [Yang, H.-X.]Department of Physics, Fuzhou University, Fuzhou, 350116, China
  • [ 4 ] [Yang, H.-X.]Center for Discrete Mathematics, Fuzhou University, Fujian, 350003, China

Reprint 's Address:

  • [Yang, H.-X.]Department of Physics, Fuzhou UniversityChina

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Source :

International Journal of Modern Physics C

ISSN: 0129-1831

Year: 2018

Issue: 4

Volume: 29

1 . 0 1 7

JCR@2018

1 . 5 0 0

JCR@2023

ESI HC Threshold:158

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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