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Evolutionary snowdrift game with an additional strategy in fully connected networks and regular lattices

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  • Zhong, Li-Xin
  • Zheng, Da-Fang
  • Zheng, Bo
  • Xu, Chen
  • Hui, P.M.

Abstract

The effects of an additional strategy or character in the evolutionary snowdrift game (SG) are studied in a well-mixed population or fully connected network and in a square lattice. The SG, which is a possible alternative to the prisoner's dilemma game in studying cooperative phenomena in competing populations, consists of two types of strategies, C (cooperators) and D (defectors). The additional L-strategy amounts to a strongly persuasive character that a fixed payoff is given to each player when a L-player is involved, regardless of the character of the opponent. In a fully connected network, it is found that either C lives with D or the L-players take over the whole population. In a square lattice, three possible situations are found: a uniform C-population, C lives with D, and the coexistence of all three characters. The presence of L-players is found to enhance cooperation in a square lattice by enhancing the payoff of cooperators. The results are discussed in terms of the effects in restricting a player to compete only with his nearest neighbors in a square lattice, as opposed to competing with all players in a fully connected network.

Suggested Citation

  • Zhong, Li-Xin & Zheng, Da-Fang & Zheng, Bo & Xu, Chen & Hui, P.M., 2007. "Evolutionary snowdrift game with an additional strategy in fully connected networks and regular lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 631-642.
    • Handle: RePEc:eee:phsmap:v:383:y:2007:i:2:p:631-642
    DOI: 10.1016/j.physa.2007.05.056
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    Cited by:

    1. Su, Lichen & Yang, Zhengzhi & Zhou, Bowen & Zhang, Naitian & Li, Yumeng, 2023. "Effects of interdependent network reciprocity on the evolution of public cooperation," Applied Mathematics and Computation, Elsevier, vol. 454(C).
    2. Deng, Yunsheng & Zhang, Jihui, 2021. "The role of the preferred neighbor with the expected payoff on cooperation in spatial public goods game under optimal strategy selection mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    3. Zhao, Jinqiu & Luo, Chao, 2019. "The effect of preferential teaching and memory on cooperation clusters in interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    4. Yunsheng Deng & Jihui Zhang, 2022. "The choice-decision based on memory and payoff favors cooperation in stag hunt game on interdependent networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(2), pages 1-13, February.
    5. Liu, Yaojun & Liu, Xingwen, 2024. "Promotion of cooperation in evolutionary snowdrift game with heterogeneous memories," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    6. Shu, Feng & Liu, Yaojun & Liu, Xingwen & Zhou, Xiaobing, 2019. "Memory-based conformity enhances cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 480-490.
    7. Xie, Kai & Liu, Xingwen & Chen, Hao & Yang, Jun, 2022. "Preferential selection and expected payoff drive cooperation in spatial voluntary public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    8. Hadzibeganovic, Tarik & Stauffer, Dietrich & Han, Xiao-Pu, 2018. "Interplay between cooperation-enhancing mechanisms in evolutionary games with tag-mediated interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 676-690.

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