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Collective Actions in Three Types of Continuous Public Goods Games in Spatial Networks

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10638))

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Abstract

Collective action in the provision of pubic goods is analyzed in the framework of three kinds of public goods dilemmas routinely encountered in real-life situations. We study the evolution of cooperation in structured populations within three PGG models: the traditional public goods game (PGG), complementary public goods game (PPGG) and containable public goods game (TPGG), differing in supplying patterns of public goods. In addition, we extend the combination of dual strategy (cooperation and defection) to a portfolio of multiple strategies. We reveal that, is a fundamental property promoting cooperation in groups of selfish individuals, irrespective of which social dilemma applies. For a parallel comparison, it is found that the system in PGG and PPGG can perform comparatively better than TPGG, which reduces the provision of the public goods. Our study can be helpful in effectively portraying the characteristics of cooperative dilemmas in real social systems.

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References

  1. Smith, J.: Evolution and the Theory of Games. Cambridge University Press, Cambridge (1982)

    Book  MATH  Google Scholar 

  2. Nowak, M.A., Sigmund, K.: Phage-lift for game theory. Nature 399, 367–368 (1999)

    Article  Google Scholar 

  3. Cleary, A.S., Leonard, T.L., Gestl, S., Gunther, E.: Tumour cell heterogeneity maintained by cooperating subclones in Wnt-driven mammary cancers. Nature 508(7494), 113–117 (2014)

    Article  Google Scholar 

  4. Xu, Z., Zhang, J., Zhang, C., Chen, Z.: Fixation of strategies driven by switching probabilities in evolutionary games. EPL (Europhys. Lett.) 116(5), 58002 (2017)

    Article  Google Scholar 

  5. Ramazi, P., Riehl, J., Cao, M.: Networks of conforming or nonconforming individuals tend to reach satisfactory decisions. Proc. Natl. Acad. Sci. 113(46), 12985–12990 (2016)

    Article  Google Scholar 

  6. Choi, W., Yook, S.H., Kim, Y.: Percolation in spatial evolutionary prisoner’s dilemma game on two-dimensional lattices. Phys. Rev. E 92(5) (2015)

    Google Scholar 

  7. Zhang, J., Zhang, C., Chu, T.: Cooperation enhanced by the survival of the fittest’ rule in prisoner’s dilemma games on complex networks. J. Theor. Biol. 267, 41–47 (2010)

    Article  MathSciNet  Google Scholar 

  8. Ghoneim, A., Abbass, H., Barlow, M.: Characterizing game dynamics in two-player strategy games using network motifs. IEEE Trans. Syst. Man Cybern. 38, 682–690 (2008)

    Article  Google Scholar 

  9. Zhao, J., Szilágyi, M., Szidarovszky, F.: An n-person battle of sexes game. Phys. A 387, 3669–3677 (2008)

    Article  MathSciNet  Google Scholar 

  10. Chan, C.H., Yin, H., Hui, P.M., Zheng, D.F.: Evolution of cooperation in well-mixed \(n\)-person snowdrift games. Phys. A 387, 2919–2925 (2008)

    Article  Google Scholar 

  11. Pacheco, J.M., Santos, F.C., Souza, M.O., Skyrms, B.: Evolutionary dynamics of collective action in \(n\)-person stag hunt dilemmas. Proc. R. Soc. Lond. B 276, 315–321 (2009)

    Article  Google Scholar 

  12. Vamvoudakis, K.G., Hespanha, J.P.: Online optimal operation of parallel voltage-source inverters using partial information. IEEE Trans. Industr. Electron. 64(5), 4296–4305 (2017)

    Article  Google Scholar 

  13. Wang, J., Hipel, K.W., Fang, L., Xu, H., Kilgour, D.M.: Behavioral analysis in the graph model for conflict resolution. IEEE Trans. Syst. Man Cybern.: Syst. (2017)

    Google Scholar 

  14. Wedekind, C., Milinski, M.: Cooperation through image scoring in humans. Science 288, 850–852 (2000)

    Article  Google Scholar 

  15. Nowak, M.A.: Five rules for the evolution of cooperation. Science 314, 1560–1563 (2006)

    Article  Google Scholar 

  16. Groot, N., De Schutter, B., Hellendoorn, H.: On systematic computation of optimal nonlinear solutions for the reverse stackelberg game. IEEE Trans. Syst. Man Cybern.: Syst. 44(10), 1315–1327 (2014)

    Article  Google Scholar 

  17. Shahrivar, E.M., Sundaram, S.: The strategic formation of multi-layer networks. IEEE Trans. Netw. Sci. Eng. 2(4), 164–178 (2015)

    Article  MathSciNet  Google Scholar 

  18. Nowak, M.A., May, R.M.: Evolutionary games and spatial chaos. Nature 359, 826–829 (1992)

    Article  Google Scholar 

  19. Weitz, J.S., Eksin, C., Paarporn, K., Brown, S.P., Ratcliff, W.C.: An oscillating tragedy of the commons in replicator dynamics with game-environment feedback. Proc. Natl. Acad. Sci. 113(47), E7518–E7525 (2016)

    Article  Google Scholar 

  20. Zhang, C., Zhang, J., Xie, G., Wang, L.: Coevolving agent strategies and network topology for the public goods games. Eur. Phys. J. B 80, 217–222 (2011)

    Article  Google Scholar 

  21. Zhang, J., Zhang, C., Cao, M., Weissing, F.: Crucial role of strategy updating for coexistence of strategies in interaction networks. Phys. Rev. E 91(4), 042101 (2015)

    Article  Google Scholar 

  22. Hauert, C., De Monte, S., Hofbauer, J., Sigmund, K.: Volunteering as Red Queen mechanism for cooperation in public goods game. Science 296, 1129–1132 (2002)

    Article  Google Scholar 

  23. Kümmerli, R., Burton-Chellew, M.N., Ross-Gillespie, A., West, S.A.: Resistance to extreme strategies, rather than prosocial preferences, can explain human cooperation in public goods games. Proc. Natl. Acad. Sci. USA 107, 10125–10130 (2010)

    Article  Google Scholar 

  24. Santos, F.C., Santos, M.D., Pacheco, J.M.: Social diversity promotes the emergence of cooperation in public goods games. Nature 454, 213–216 (2008)

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61603199, 61603201 and 61573199), and the Foundation of Key Laboratory of Machine Intelligence and Advanced Computing of the Ministry of Education (Grant No. MSC-201709A).

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Correspondence to Jianlei Zhang .

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Xu, Z., Li, Q., Zhang, J. (2017). Collective Actions in Three Types of Continuous Public Goods Games in Spatial Networks. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10638. Springer, Cham. https://doi.org/10.1007/978-3-319-70139-4_69

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  • DOI: https://doi.org/10.1007/978-3-319-70139-4_69

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-70139-4

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