Skip to main content
Log in

Cooperation of improved HK networks based on prisoner dilemma game

  • Foundations
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

To model the cooperative behavior under the realistic world, we put forward a high-clustering network model with the property of adjustable power-law, and analyze the evolution of the prisoner dilemma game on this improved HK network model. Using simulation experiments, we investigate the effect of high clustering property of this network on the cooperative behavior. Extensive simulations indicate that a high value of the clustering coefficient may greatly contribute to the emergence of cooperative behavior. We also find that with the increase in the temptation parameter, the level of cooperation will decrease, but the variation range is not wide. Altogether, this evolutionary game model can promote the emergence of cooperative phenomenon by resisting the spread of the betrayal strategy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Barabási AL, Albert R, Jeong H (1999) Mean-field theory for scale-free random networks. Phys A Stat Mech Appl 272:173–187

    Article  Google Scholar 

  • Chen LQ, Gao JC, Xie G, Liu H.Y, L YA(2015) Routing to enhance traffic capacity for scale-free networks with tunable clustering. In: Advanced information technology, electronic and automation control conference. Chongqing, pp 110–113

  • Cui AX, Fu Y (2015) Accelerated-growth HK network evolution model. Comput Sci 42:37–39

    Google Scholar 

  • Gómezgardeñes J, Campillo M, Floría LM, Moreno Y (2007) Dynamical organization of cooperation in complex topologies. Phys Rev Lett 98:108103

    Article  Google Scholar 

  • Holme P, Kim BJ (2001) Growing scale-free networks with tunable clustering. Phys Rev E Stat Nonlinear Soft Matter Phys 65:95–129

    Google Scholar 

  • Huang ZG, Liu SL, Mao XP, Chen KF, Li J (2017) Insight of the protection for data security under selective opening attacks. Inf Sci 412–413:223–241

    Article  Google Scholar 

  • Li WG, Wang LH, Chen MF (2009) Study and improvement on growing HK network model. Comput Eng 35:121–122

    Google Scholar 

  • Li PP, Ke JH, Lin ZQ, Hui PM (2012) Cooperative behavior in evolutionary snowdrift games with the unconditional imitation rule on regular lattices. Phys Rev E 85:287–300

    Google Scholar 

  • Li J, Yan HY, Liu ZL, Chen XF, Huang XY, Wong DS (2015a) Location-sharing systems with enhanced privacy. IEEE Syst J Mob Online Soc Netw 11:1–10

    Google Scholar 

  • Li RQ, Sun SW, Ma YL, Wang L, Xia CY (2015b) Effect of clustering on attack vulnerability of interdependent scale-free networks. Chaos Solitons Fractals 80:109–116

    Article  MathSciNet  Google Scholar 

  • Li P, Li J, Huang Z, Li T, Gao CZ, Yiu SM, Chen K (2017a) Multi-key privacy-preserving deep learning in cloud computing. Future Gen Comput Syst 74:76–85

    Article  Google Scholar 

  • Li P, Li J, Huang Z, Gao CZ, Chen WB, Chen K (2017b) Privacy-preserving outsourced classification in cloud computing. Clust Comput 1–10

  • Luo C, Zhang XL, Liu H, Shao R (2016) Cooperation in memory-based prisoner’s dilemma game on interdependent networks. Phys A Stat Mech Appl 450:560–569

    Article  Google Scholar 

  • Meng XK, Sun SW, Li XX, Wang L, Xia CY, Sun JQ (2016) Interdependency enriches the spatial reciprocity in prisoner’s dilemma game on weighted networks. Phys A Stat Mech Appl 441:388–396

    Article  Google Scholar 

  • Nowak MA, May RM (1992) Evolutionary games and spatial chaos. Nature 359:826–829

    Article  Google Scholar 

  • Santos FC, Pacheco JM (2005) Scale-free networks provide a unifying framework for the emergence of cooperation. Phys Rev Lett 95:098104

    Article  Google Scholar 

  • Song YP, Ni J (2016) Effect of variable network clustering on the accuracy of node centrality. Acta Phys Sin 65:375–382

    Google Scholar 

  • Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’networks. Nature 393:440–442

    Article  Google Scholar 

  • Xu YZ, Zhang DM, Zeng C, Sun YQ (2016) Research on and modeling of the improved HK network model. Electron Sci Tech 29:106–109

    Google Scholar 

  • Zhang XJ, G B, Guan XM, Zhu YB, Lv RL (2016) Cascading failure in scale-free networks with tunable clustering. Int J Mod Phys C 27:1650093–1650093

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yunsheng Deng.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standard

This article does not contain any studies with human participants performed by any of the authors.

Additional information

Communicated by A. Di Nola.

Project supported by the National Natural Science Foundation of China (Grants Nos. 61673200, 61502218 and 61472172) and by the Natural Science Foundation of Shandong Province of China (Grant No. BS2014DX016).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Deng, Y., Miao, P. & Yang, H. Cooperation of improved HK networks based on prisoner dilemma game. Soft Comput 22, 7893–7899 (2018). https://doi.org/10.1007/s00500-018-3055-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-018-3055-7

Keywords

Navigation