IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v392y2013i13p2886-2892.html
   My bibliography  Save this article

General conditions for strategy abundance through a self-referential mechanism under weak selection

Author

Listed:
  • Sekiguchi, Takuya

Abstract

We examine stochastic evolutionary game dynamics of two-player m×m symmetric and m×n asymmetric games in finite populations assuming that a player decides to change her current strategy on the basis of her dissatisfaction, which we call a self-referential mechanism. We derive the general expression for the stationary distribution of strategy under weak selection and compare it with the counterpart of a Moran process. As a result, we find that both in symmetric games and in asymmetric games, the self-referential mechanism always generates a greater gap between the favored and unfavored strategies’ frequencies for a fixed parameter set than does a Moran process. Further, we found that for small mutation rates, our results are almost identical to the counterpart of a Moran process.

Suggested Citation

  • Sekiguchi, Takuya, 2013. "General conditions for strategy abundance through a self-referential mechanism under weak selection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(13), pages 2886-2892.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:13:p:2886-2892
    DOI: 10.1016/j.physa.2013.03.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437113002070
    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.2013.03.004?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. Hisashi Ohtsuki & Christoph Hauert & Erez Lieberman & Martin A. Nowak, 2006. "A simple rule for the evolution of cooperation on graphs and social networks," Nature, Nature, vol. 441(7092), pages 502-505, May.
    2. Martin A. Nowak & Akira Sasaki & Christine Taylor & Drew Fudenberg, 2004. "Emergence of cooperation and evolutionary stability in finite populations," Nature, Nature, vol. 428(6983), pages 646-650, April.
    3. Fudenberg, Drew & Imhof, Lorens A., 2006. "Imitation processes with small mutations," Journal of Economic Theory, Elsevier, vol. 131(1), pages 251-262, November.
    4. Binmore, Ken & Samuelson, Larry, 1997. "Muddling Through: Noisy Equilibrium Selection," Journal of Economic Theory, Elsevier, vol. 74(2), pages 235-265, June.
    5. Lin, Ying-Ting & Yang, Han-Xin & Wu, Zhi-Xi & Wang, Bing-Hong, 2011. "Promotion of cooperation by aspiration-induced migration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(1), pages 77-82.
    6. C. Hadjichrysanthou & M. Broom & J. Rychtář, 2011. "Evolutionary Games on Star Graphs Under Various Updating Rules," Dynamic Games and Applications, Springer, vol. 1(3), pages 386-407, September.
    7. Kurokawa, Shun & Wakano, Joe Yuichiro & Ihara, Yasuo, 2010. "Generous cooperators can outperform non-generous cooperators when replacing a population of defectors," Theoretical Population Biology, Elsevier, vol. 77(4), pages 257-262.
    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. Takuya Sekiguchi & Hisashi Ohtsuki, 2017. "Fixation Probabilities of Strategies for Bimatrix Games in Finite Populations," Dynamic Games and Applications, Springer, vol. 7(1), pages 93-111, March.
    2. Takuya Sekiguchi, 2023. "Fixation Probabilities of Strategies for Trimatrix Games and Their Applications to Triadic Conflict," Dynamic Games and Applications, Springer, vol. 13(3), pages 1005-1033, September.
    3. Quan, Ji & Liu, Wei & Chu, Yuqing & Wang, Xianjia, 2018. "Stochastic dynamics and stable equilibrium of evolutionary optional public goods game in finite populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 123-134.
    4. Marta C. Couto & Saptarshi Pal, 2023. "Introspection Dynamics in Asymmetric Multiplayer Games," Dynamic Games and Applications, Springer, vol. 13(4), pages 1256-1285, December.
    5. Sekiguchi, Takuya, 2023. "Abundance of strategies for trimatrix games in finite populations," Applied Mathematics and Computation, Elsevier, vol. 448(C).

    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. Sandholm, William H., 2012. "Stochastic imitative game dynamics with committed agents," Journal of Economic Theory, Elsevier, vol. 147(5), pages 2056-2071.
    2. Zhang, Huanren, 2018. "Errors can increase cooperation in finite populations," Games and Economic Behavior, Elsevier, vol. 107(C), pages 203-219.
    3. Kroumi, Dhaker & Lessard, Sabin, 2015. "Evolution of cooperation in a multidimensional phenotype space," Theoretical Population Biology, Elsevier, vol. 102(C), pages 60-75.
    4. Dhaker Kroumi, 2021. "Aspiration Can Promote Cooperation in Well-Mixed Populations As in Regular Graphs," Dynamic Games and Applications, Springer, vol. 11(2), pages 390-417, June.
    5. Tsakas Nikolas, 2014. "Imitating the Most Successful Neighbor in Social Networks," Review of Network Economics, De Gruyter, vol. 12(4), pages 403-435, February.
    6. Fudenberg, Drew & Imhof, Lorens A., 2008. "Monotone imitation dynamics in large populations," Journal of Economic Theory, Elsevier, vol. 140(1), pages 229-245, May.
    7. Izquierdo, Luis R. & Izquierdo, Segismundo S. & Sandholm, William H., 2019. "An introduction to ABED: Agent-based simulation of evolutionary game dynamics," Games and Economic Behavior, Elsevier, vol. 118(C), pages 434-462.
    8. Benjamin Allen & Christine Sample & Robert Jencks & James Withers & Patricia Steinhagen & Lori Brizuela & Joshua Kolodny & Darren Parke & Gabor Lippner & Yulia A Dementieva, 2020. "Transient amplifiers of selection and reducers of fixation for death-Birth updating on graphs," PLOS Computational Biology, Public Library of Science, vol. 16(1), pages 1-20, January.
    9. Alex McAvoy & Andrew Rao & Christoph Hauert, 2021. "Intriguing effects of selection intensity on the evolution of prosocial behaviors," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-21, November.
    10. Dhaker Kroumi & Sabin Lessard, 2015. "Conditions for Cooperation to be More Abundant than Defection in a Hierarchically Structured Population," Dynamic Games and Applications, Springer, vol. 5(2), pages 239-262, June.
    11. Konrad, Kai A. & Morath, Florian, 2020. "The Volunteer’s Dilemma in Finite Populations," CEPR Discussion Papers 15536, C.E.P.R. Discussion Papers.
    12. Peng Liu & Haoxiang Xia, 2015. "Structure and evolution of co-authorship network in an interdisciplinary research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 101-134, April.
    13. John T. Scholz & Cheng‐Lung Wang, 2009. "Learning to Cooperate: Learning Networks and the Problem of Altruism," American Journal of Political Science, John Wiley & Sons, vol. 53(3), pages 572-587, July.
    14. 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).
    15. Lessard, Sabin & Lahaie, Philippe, 2009. "Fixation probability with multiple alleles and projected average allelic effect on selection," Theoretical Population Biology, Elsevier, vol. 75(4), pages 266-277.
    16. Bin Wu & Julián García & Christoph Hauert & Arne Traulsen, 2013. "Extrapolating Weak Selection in Evolutionary Games," PLOS Computational Biology, Public Library of Science, vol. 9(12), pages 1-7, December.
    17. Ellison, Glenn & Fudenberg, Drew & Imhof, Lorens A., 2009. "Random matching in adaptive dynamics," Games and Economic Behavior, Elsevier, vol. 66(1), pages 98-114, May.
    18. Marta C. Couto & Saptarshi Pal, 2023. "Introspection Dynamics in Asymmetric Multiplayer Games," Dynamic Games and Applications, Springer, vol. 13(4), pages 1256-1285, December.
    19. Wakano, Joe Yuichiro & Ohtsuki, Hisashi & Kobayashi, Yutaka, 2013. "A mathematical description of the inclusive fitness theory," Theoretical Population Biology, Elsevier, vol. 84(C), pages 46-55.
    20. Hao, Weijuan & Hu, Yuhan, 2024. "The implications of deep cooperation strategy for the evolution of cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 470(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:392:y:2013:i:13:p:2886-2892. 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.