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Evolutionary snowdrift game with rational selection based on radical evaluation

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  • Ye, Wenxing
  • Fan, Suohai

Abstract

Considering some phenomena observed in the real world, we introduce a rational selecting mechanism based on radical evaluation into evolutionary snowdrift game. In the proposed model, players are endowed with a sense of rationality, which helps evaluate behaviors radically and select neighbors with different attractiveness. Those neighbors who made a preferable strategy and got more payoffs compared with the anti-strategy will have more attractiveness as references. It is found that the selection based on radical evaluation significantly enhances the level of cooperation on regular networks with large neighborhood size K and scale-free networks over a wide range of cost-to-benefit ratio r. Discussions for the transition of spatial patterns and strategy degree distribution at some critical values of the payoff parameter show the effects of the proposed selecting mechanism. The findings may be helpful in understanding cooperative behavior in natural and social systems consisting of rational selection with radical evaluation.

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  • Ye, Wenxing & Fan, Suohai, 2017. "Evolutionary snowdrift game with rational selection based on radical evaluation," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 310-317.
  • Handle: RePEc:eee:apmaco:v:294:y:2017:i:c:p:310-317
    DOI: 10.1016/j.amc.2016.09.007
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    1. A. Szolnoki & M. Perc & G. Szabó, 2008. "Diversity of reproduction rate supports cooperation in the prisoner's dilemma game on complex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(4), pages 505-509, February.
    2. Zhang, Gui-Qing & Hu, Tao-Ping & Yu, Zi, 2016. "An improved fitness evaluation mechanism with noise in prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 276(C), pages 31-36.
    3. Neil Johnson & Thomas Lux, 2011. "Ecology and economics," Nature, Nature, vol. 469(7330), pages 302-303, January.
    4. Wang, Xu-Wen & Wang, Zhen & Nie, Sen & Jiang, Luo-Luo & Wang, Bing-Hong, 2015. "Impact of keeping silence on spatial reciprocity in spatial games," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 848-853.
    5. Jia, Ning & Ma, Shoufeng, 2013. "Evolution of cooperation in the snowdrift game among mobile players with random-pairing and reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5700-5710.
    6. Christoph Hauert & Michael Doebeli, 2004. "Spatial structure often inhibits the evolution of cooperation in the snowdrift game," Nature, Nature, vol. 428(6983), pages 643-646, April.
    7. Chen, Mei-huan & Wang, Li & Wang, Juan & Sun, Shi-wen & Xia, Cheng-yi, 2015. "Impact of individual response strategy on the spatial public goods game within mobile agents," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 192-202.
    8. Zhang, Jun & Fang, Yi-Ping & Du, Wen-Bo & Cao, Xian-Bin, 2011. "Promotion of cooperation in aspiration-based spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2258-2266.
    9. Shi, Yong-Dong & Zhong, Li-Xin & Xu, Wen-Juan, 2013. "Effects of group sensitivity on cooperation in N-person snowdrift game with dynamic grouping," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 132-138.
    10. Huang, Keke & Zheng, Xiaoping & Su, Yunpeng, 2015. "Effect of heterogeneous sub-populations on the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 681-687.
    11. Xu, Meng & Zheng, Da-Fang & Xu, C. & Zhong, Lixin & Hui, P.M., 2015. "Cooperative behavior in N-person evolutionary snowdrift games with punishment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 322-329.
    12. M. Sysi-Aho & J. Saramäki & J. Kertész & K. Kaski, 2005. "Spatial snowdrift game with myopic agents," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 44(1), pages 129-135, March.
    13. Wang, Xu-Wen & Jiang, Luo-Luo & Nie, Sen & Wang, Bing-Hong, 2015. "Uncovering cooperative behaviors with sparse historical behavior data in the spatial games," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 317-322.
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