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Robustness of cooperation in memory-based prisoner’s dilemma game on a square lattice

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  • Ren, Guangming
  • Wang, Xingyuan
Abstract
Cooperation in prisoner’s dilemma game can be promoted significantly by introducing memory effects. In this work, we assume that the changing probability of strategy is determined by the agents’ accumulative payoff in all time steps. We have numerically investigated robustness of cooperation by introducing an attack probability, with which an individual in cooperation clusters becomes a defector. It is found that the density of cooperators at stable states decreases with the attack probability in traditional memoryless models. However, in the memory-based model, the density of cooperators cannot reach a stable state even if the attack probability is very small. The more the increase of the attack probability, the faster the vanishment of the cooperators. Our work could be helpful to understand the emergence of cooperation in systems consisting of selfish individuals. It suggests a new method to study whether cooperation can be maintained in noisy environments.

Suggested Citation

  • Ren, Guangming & Wang, Xingyuan, 2014. "Robustness of cooperation in memory-based prisoner’s dilemma game on a square lattice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 40-46.
    • Handle: RePEc:eee:phsmap:v:408:y:2014:i:c:p:40-46
    DOI: 10.1016/j.physa.2014.04.022
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    References listed on IDEAS

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    1. Wang, Tao & Chen, Zhigang & Li, Kenli & Deng, Xiaoheng & Li, Deng, 2014. "Memory does not necessarily promote cooperation in dilemma games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 218-227.
    2. Nicola Dimitri, 2000. "Correlation, Learning and the Robustness of Cooperation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(2), pages 311-329, April.
    3. Liu, Yongkui & Li, Zhi & Chen, Xiaojie & Wang, Long, 2010. "Memory-based prisoner’s dilemma on square lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2390-2396.
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    Cited by:

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    2. Hu, Xiang & Liu, Xingwen & Zhou, Xiaobing, 2022. "A proportional-neighborhood-diversity evolution in snowdrift game on square lattice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
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    6. Huang, Chaochao & Wang, Chaoqian, 2024. "Memory-based involution dilemma on square lattices," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    7. Luo, Chao & Zhang, Xiaolin & Liu, Hong & Shao, Rui, 2016. "Cooperation in memory-based prisoner’s dilemma game on interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 560-569.
    8. Schimit, P.H.T. & Santos, B.O. & Soares, C.A., 2015. "Evolution of cooperation in Axelrod tournament using cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 204-217.
    9. 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.
    10. Zhang, Hong, 2015. "Moderate tolerance promotes tag-mediated cooperation in spatial Prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 52-61.
    11. Dong, Yukun & Xu, Hedong & Fan, Suohai, 2019. "Memory-based stag hunt game on regular lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 247-255.
    12. Shu, Feng & Liu, Xingwen & Fang, Kai & Chen, Hao, 2018. "Memory-based snowdrift game on a square lattice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 15-26.
    13. Liu, Penghui & Liu, Jing, 2017. "Robustness of coevolution in resolving prisoner’s dilemma games on interdependent networks subject to attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 362-370.

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