IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v395y2014icp218-227.html
   My bibliography  Save this article

Memory does not necessarily promote cooperation in dilemma games

Author

Listed:
  • Wang, Tao
  • Chen, Zhigang
  • Li, Kenli
  • Deng, Xiaoheng
  • Li, Deng

Abstract

Evolutionary games can model dilemmas for which cooperation can exist in rational populations. According to intuition, memory of the history can help individuals to overcome the dilemma and increase cooperation. However, here we show that no such general predictions can be made for dilemma games with memory. Agents play repeated prisoner’s dilemma, snowdrift, or stag hunt games in well-mixed populations or on a lattice. We compare the cooperation ratio and fitness for systems with or without memory. An interesting result is that cooperation is demoted in snowdrift and stag hunt games with memory when cost-to-benefit ratio is low, while system fitness still increases with memory in the snowdrift game. To illustrate this interesting phenomenon, two further experiments were performed to study R, ST, and P reciprocity and investigate 16 agent strategies for one-step memory. The results show that memory plays different roles in different dilemma games.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:395:y:2014:i:c:p:218-227
    DOI: 10.1016/j.physa.2013.10.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437113009850
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2013.10.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ramón Alonso-Sanz & Margarita Martín, 2006. "Memory Boosts Cooperation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 841-852.
    2. Chen, Xiaojie & Fu, Feng & Wang, Long, 2008. "Promoting cooperation by local contribution under stochastic win-stay-lose-shift mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5609-5615.
    3. Imhof, Lorens & Nowak, Martin & Fudenberg, Drew, 2007. "Tit-for-Tat or Win-Stay, Lose-Shift?," Scholarly Articles 3200671, Harvard University Department of Economics.
    4. 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.
    5. Deng, Xiao-Heng & Liu, Yi & Chen, Zhi-Gang, 2010. "Memory-based evolutionary game on small-world network with tunable heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5173-5181.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhu, Jiabao & Liu, Xingwen, 2021. "The number of strategy changes can be used to promote cooperation in spatial snowdrift game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 575(C).
    2. Xu, Liang & Cao, Xianbin & Du, Wenbo & Li, Yumeng, 2018. "Effects of taxation on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 63-68.
    3. 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).
    4. Han, Dun & Sun, Mei, 2014. "Can memory and conformism resolve the vaccination dilemma?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 95-104.
    5. Huang, Chaochao & Wang, Chaoqian, 2024. "Memory-based involution dilemma on square lattices," Chaos, Solitons & Fractals, Elsevier, vol. 178(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. Shu, Feng & Li, Min & Liu, Xingwen, 2019. "Memory mechanism with weighting promotes cooperation in the evolutionary games," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 17-24.
    8. 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.
    9. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yongkui Liu & Xiaojie Chen & Lin Zhang & Long Wang & Matjaž Perc, 2012. "Win-Stay-Lose-Learn Promotes Cooperation in the Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    2. Chen, Zhi-Gang & Wang, Tao & Xiao, De-Gui & Xu, Yin, 2013. "Can remembering history from predecessor promote cooperation in the next generation?," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 59-68.
    3. Wang, Xu-Wen & Nie, Sen & Jiang, Luo-Luo & Wang, Bing-Hong & Chen, Shi-Ming, 2017. "Role of delay-based reward in the spatial cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 153-158.
    4. Zhao, Zhengwu & Zhang, Chunyan, 2023. "The mechanisms of labor division from the perspective of task urgency and game theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    5. Zha, Jiajing & Li, Cong & Fan, Suohai, 2022. "The effect of stability-based strategy updating on cooperation in evolutionary social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 413(C).
    6. Chang, Shuhua & Zhang, Zhipeng & Wu, Yu’e & Xie, Yunya, 2018. "Cooperation is enhanced by inhomogeneous inertia in spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 419-425.
    7. Huang, Chaochao & Wang, Chaoqian, 2024. "Memory-based involution dilemma on square lattices," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    8. Li, Xiaopeng & Han, Weiwei & Yang, Wenjun & Wang, Juan & Xia, Chengyi & Li, Hui-jia & Shi, Yong, 2022. "Impact of resource-based conditional interaction on cooperation in spatial social dilemmas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    9. Su, Qi & Li, Aming & Wang, Long, 2017. "Spatial structure favors cooperative behavior in the snowdrift game with multiple interactive dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 299-306.
    10. Ji, Jiezhou & Pan, Qiuhui & Zhu, Wenqiang & He, Mingfeng, 2023. "The influence of own historical information and environmental historical information on the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 446(C).
    11. Li, Minlan & Liu, Yan-Ping & Han, Yanyan & Wang, Rui-Wu, 2022. "Environmental heterogeneity unifies the effect of spatial structure on the altruistic cooperation in game-theory paradigms," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    12. Mike Farjam & Wladislaw Mill & Marian Panganiban, 2016. "Ignorance Is Bliss, But for Whom? The Persistent Effect of Good Will on Cooperation," Games, MDPI, vol. 7(4), pages 1-19, October.
    13. Zhang, Jing & Li, Zhao & Zhang, Jiqiang & Ma, Lin & Zheng, Guozhong & Chen, Li, 2023. "Emergence of oscillatory cooperation in a population with incomplete information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    14. Liu, Yongkui & Chen, Xiaojie & Zhang, Lin & Tao, Fei & Wang, Long, 2012. "Does migration cost influence cooperation among success-driven individuals?," Chaos, Solitons & Fractals, Elsevier, vol. 45(11), pages 1301-1308.
    15. 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.
    16. 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.
    17. Guo, Tian & Du, Chunpeng & Shi, Lei, 2024. "Evolution of cooperation on interdependent networks: The impact of asymmetric punishment," Applied Mathematics and Computation, Elsevier, vol. 463(C).
    18. Deng, Zhenghong & Ma, Chunmiao & Mao, Xudong & Wang, Shenglan & Niu, Zhenxi & Gao, Li, 2017. "Historical payoff promotes cooperation in the prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 1-5.
    19. Wang, Chaoqian & Huang, Chaochao, 2022. "Between local and global strategy updating in public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    20. 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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:395:y:2014:i:c:p:218-227. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.