IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v390y2011i23p4502-4513.html
   My bibliography  Save this article

The influence of tie strength on evolutionary games on networks: An empirical investigation

Author

Listed:
  • Buesser, Pierre
  • Peña, Jorge
  • Pestelacci, Enea
  • Tomassini, Marco

Abstract

Extending previous work on unweighted networks, we present here a systematic numerical investigation of standard evolutionary games on weighted networks. In the absence of any reliable model for generating weighted social networks, we attribute weights to links in a few ways supported by empirical data ranging from totally uncorrelated to weighted bipartite networks. The results of the extensive simulation work on standard complex network models show that, except in a case that does not seem to be common in social networks, taking the tie strength into account does not change in a radical manner the long-run steady-state behavior of the studied games. Besides model networks, we also included a real-life case drawn from a coauthorship network. In this case also, taking the weights into account only changes the results slightly with respect to the raw unweighted graph, although to draw more reliable conclusions on real social networks many more cases should be studied as these weighted networks become available.

Suggested Citation

  • Buesser, Pierre & Peña, Jorge & Pestelacci, Enea & Tomassini, Marco, 2011. "The influence of tie strength on evolutionary games on networks: An empirical investigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4502-4513.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:23:p:4502-4513
    DOI: 10.1016/j.physa.2011.07.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437111005681
    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.2011.07.021?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. Vega-Redondo,Fernando, 2003. "Economics and the Theory of Games," Cambridge Books, Cambridge University Press, number 9780521775908, January.
    2. Francisco C Santos & Jorge M Pacheco & Tom Lenaerts, 2006. "Cooperation Prevails When Individuals Adjust Their Social Ties," PLOS Computational Biology, Public Library of Science, vol. 2(10), pages 1-8, October.
    3. Du, Wen-Bo & Zheng, Hao-Ran & Hu, Mao-Bin, 2008. "Evolutionary prisoner’s dilemma game on weighted scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3796-3800.
    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. Barthélemy, Marc & Barrat, Alain & Pastor-Satorras, Romualdo & Vespignani, Alessandro, 2005. "Characterization and modeling of weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(1), pages 34-43.
    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. Iwata, Manabu & Akiyama, Eizo, 2016. "Heterogeneity of link weight and the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 224-234.
    2. 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.

    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. Luthi, Leslie & Pestelacci, Enea & Tomassini, Marco, 2008. "Cooperation and community structure in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 955-966.
    2. Yang, Zhengzhi & Zheng, Lei & Perc, Matjaž & Li, Yumeng, 2024. "Interaction state Q-learning promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 463(C).
    3. Zhang, Hui & Wang, Li & Hou, Dongshuang, 2016. "Effect of the spatial autocorrelation of empty sites on the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 296-308.
    4. Sun, Jiaqin & Fan, Ruguo & Luo, Ming & Zhang, Yingqing & Dong, Lili, 2018. "The evolution of cooperation in spatial prisoner’s dilemma game with dynamic relationship-based preferential learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 598-611.
    5. Chen, Zhuo & Gao, Jianxi & Cai, Yunze & Xu, Xiaoming, 2011. "Evolutionary prisoner’s dilemma game in flocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(1), pages 50-56.
    6. Deng, Zheng-Hong & Huang, Yi-Jie & Gu, Zhi-Yang & Li-Gao,, 2018. "Multigames with social punishment and the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 164-170.
    7. Scatà, Marialisa & Di Stefano, Alessandro & La Corte, Aurelio & Liò, Pietro & Catania, Emanuele & Guardo, Ermanno & Pagano, Salvatore, 2016. "Combining evolutionary game theory and network theory to analyze human cooperation patterns," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 17-24.
    8. Luis R. Izquierdo & Segismundo S. Izquierdo & José Manuel Galán & José Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-6.
    9. Markus Brede, 2013. "Costly Advertising and the Evolution of Cooperation," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
    10. Wes Maciejewski & Feng Fu & Christoph Hauert, 2014. "Evolutionary Game Dynamics in Populations with Heterogenous Structures," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-16, April.
    11. Swami Iyer & Timothy Killingback, 2020. "Evolution of Cooperation in Social Dilemmas with Assortative Interactions," Games, MDPI, vol. 11(4), pages 1-31, September.
    12. Michael Foley & Rory Smead & Patrick Forber & Christoph Riedl, 2021. "Avoiding the bullies: The resilience of cooperation among unequals," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.
    13. Xiaojie Chen & Alana Schick & Michael Doebeli & Alistair Blachford & Long Wang, 2012. "Reputation-Based Conditional Interaction Supports Cooperation in Well-Mixed Prisoner’s Dilemmas," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-7, May.
    14. Te Wu & Feng Fu & Long Wang, 2011. "Moving Away from Nasty Encounters Enhances Cooperation in Ecological Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-7, November.
    15. Chen, Zhuo & Gao, Jianxi & Cai, Yunze & Xu, Xiaoming, 2011. "Evolution of cooperation among mobile agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(9), pages 1615-1622.
    16. Shijun Wang & Máté S Szalay & Changshui Zhang & Peter Csermely, 2008. "Learning and Innovative Elements of Strategy Adoption Rules Expand Cooperative Network Topologies," PLOS ONE, Public Library of Science, vol. 3(4), pages 1-9, April.
    17. Kohei Miyaji & Jun Tanimoto & Zhen Wang & Aya Hagishima & Naoki Ikegaya, 2013. "Direct Reciprocity in Spatial Populations Enhances R-Reciprocity As Well As ST-Reciprocity," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    18. Du, Faqi & Fu, Feng, 2013. "Quantifying the impact of noise on macroscopic organization of cooperation in spatial games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 35-44.
    19. Zhong, Weicai & Abbass, Hussein A. & Bender, Axel & Liu, Jing, 2011. "Mixed strategy and coevolution dynamics in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 410-417.
    20. Zhang, Hui & Zhang, Feng & Li, Zizhen & Gao, Meng & Li, Wenlong, 2009. "Evolutionary diversity and spatiotemporal dynamics of a spatial game," Ecological Modelling, Elsevier, vol. 220(19), pages 2353-2364.

    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:390:y:2011:i:23:p:4502-4513. 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.