IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0204981.html
   My bibliography  Save this article

Evolution reinforces cooperation with the emergence of self-recognition mechanisms: An empirical study of strategies in the Moran process for the iterated prisoner’s dilemma

Author

Listed:
  • Vincent Knight
  • Marc Harper
  • Nikoleta E Glynatsi
  • Owen Campbell

Abstract

We present insights and empirical results from an extensive numerical study of the evolutionary dynamics of the iterated prisoner’s dilemma. Fixation probabilities for Moran processes are obtained for all pairs of 164 different strategies including classics such as TitForTat, zero determinant strategies, and many more sophisticated strategies. Players with long memories and sophisticated behaviours outperform many strategies that perform well in a two player setting. Moreover we introduce several strategies trained with evolutionary algorithms to excel at the Moran process. These strategies are excellent invaders and resistors of invasion and in some cases naturally evolve handshaking mechanisms to resist invasion. The best invaders were those trained to maximize total payoff while the best resistors invoke handshake mechanisms. This suggests that while maximizing individual payoff can lead to the evolution of cooperation through invasion, the relatively weak invasion resistance of payoff maximizing strategies are not as evolutionarily stable as strategies employing handshake mechanisms.

Suggested Citation

  • Vincent Knight & Marc Harper & Nikoleta E Glynatsi & Owen Campbell, 2018. "Evolution reinforces cooperation with the emergence of self-recognition mechanisms: An empirical study of strategies in the Moran process for the iterated prisoner’s dilemma," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-33, October.
    • Handle: RePEc:plo:pone00:0204981
    DOI: 10.1371/journal.pone.0204981
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0204981
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0204981&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0204981?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
    ---><---

    References listed on IDEAS

    as
    1. Benjamin Allen & Gabor Lippner & Yu-Ting Chen & Babak Fotouhi & Naghmeh Momeni & Shing-Tung Yau & Martin A. Nowak, 2017. "Evolutionary dynamics on any population structure," Nature, Nature, vol. 544(7649), pages 227-230, April.
    2. Banks, Jeffrey S. & Sundaram, Rangarajan K., 1990. "Repeated games, finite automata, and complexity," Games and Economic Behavior, Elsevier, vol. 2(2), pages 97-117, June.
    3. Merrill M. Flood, 1958. "Some Experimental Games," Management Science, INFORMS, vol. 5(1), pages 5-26, October.
    4. Christoph Adami & Arend Hintze, 2013. "Evolutionary instability of zero-determinant strategies demonstrates that winning is not everything," Nature Communications, Nature, vol. 4(1), pages 1-8, October.
    5. Christian Hilbe & Martin A Nowak & Arne Traulsen, 2013. "Adaptive Dynamics of Extortion and Compliance," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-9, November.
    6. Christopher Lee & Marc Harper & Dashiell Fryer, 2015. "The Art of War: Beyond Memory-one Strategies in Population Games," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-16, March.
    7. Nachbar, John H., 1992. "Evolution in the finitely repeated prisoner's dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 19(3), pages 307-326, December.
    8. Marc Harper & Vincent Knight & Martin Jones & Georgios Koutsovoulos & Nikoleta E Glynatsi & Owen Campbell, 2017. "Reinforcement learning produces dominant strategies for the Iterated Prisoner’s Dilemma," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-33, December.
    Full references (including those not matched with items on IDEAS)

    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. Marc Harper & Vincent Knight & Martin Jones & Georgios Koutsovoulos & Nikoleta E Glynatsi & Owen Campbell, 2017. "Reinforcement learning produces dominant strategies for the Iterated Prisoner’s Dilemma," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-33, December.
    2. Masahiko Ueda & Toshiyuki Tanaka, 2020. "Linear algebraic structure of zero-determinant strategies in repeated games," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-13, April.
    3. Christopher Lee & Marc Harper & Dashiell Fryer, 2015. "The Art of War: Beyond Memory-one Strategies in Population Games," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-16, March.
    4. Quan, Ji & Chen, Xinyue & Wang, Xianjia, 2024. "Repeated prisoner's dilemma games in multi-player structured populations with crosstalk," Applied Mathematics and Computation, Elsevier, vol. 473(C).
    5. Samuelson, Larry, 1996. "Bounded rationality and game theory," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 17-35.
    6. Christopher Graser & Takako Fujiwara-Greve & Julian García & Matthijs van Veelen, 2024. "Repeated games with partner choice," Tinbergen Institute Discussion Papers 24-038/I, Tinbergen Institute.
    7. Kang, Kai & Tian, Jinyan & Zhang, Boyu, 2024. "Cooperation and control in asymmetric repeated games," Applied Mathematics and Computation, Elsevier, vol. 470(C).
    8. Nikoleta E. Glynatsi & Vincent A. Knight, 2021. "A bibliometric study of research topics, collaboration, and centrality in the iterated prisoner’s dilemma," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-12, December.
    9. Ueda, Masahiko, 2023. "Memory-two strategies forming symmetric mutual reinforcement learning equilibrium in repeated prisoners’ dilemma game," Applied Mathematics and Computation, Elsevier, vol. 444(C).
    10. Yali Dong & Cong Li & Yi Tao & Boyu Zhang, 2015. "Evolution of Conformity in Social Dilemmas," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-12, September.
    11. Taha, Mohammad A. & Ghoneim, Ayman, 2021. "Zero-determinant strategies in infinitely repeated three-player prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    12. Westhoff, Frank H. & Yarbrough, Beth V. & Yarbrough, Robert M., 1996. "Complexity, organization, and Stuart Kauffman's The Origins of Order," Journal of Economic Behavior & Organization, Elsevier, vol. 29(1), pages 1-25, January.
    13. Yohsuke Murase & Seung Ki Baek, 2021. "Friendly-rivalry solution to the iterated n-person public-goods game," PLOS Computational Biology, Public Library of Science, vol. 17(1), pages 1-17, January.
    14. Tatiana Kozitsina & Anna Mikhaylova & Anna Komkova & Anastasia Peshkovskaya & Anna Sedush & Olga Menshikova & Mikhail Myagkov & Ivan Menshikov, 2020. "Ethnicity and gender influence the decision making in a multinational state: The case of Russia," Papers 2012.01272, arXiv.org.
    15. M. Kleshnina & K. Kaveh & K. Chatterjee, 2020. "The role of behavioural plasticity in finite vs infinite populations," Papers 2009.13160, arXiv.org.
    16. Maier-Rigaud, Frank P. & Apesteguia, José, 2003. "The Role of Choice in Social Dilemma Experiments," Bonn Econ Discussion Papers 22/2003, University of Bonn, Bonn Graduate School of Economics (BGSE).
    17. van Damme, E.E.C., 1995. "Game theory : The next stage," Other publications TiSEM 7779b0f9-bef5-45c7-ae6b-7, Tilburg University, School of Economics and Management.
    18. Andrew M. Colman & Briony D. Pulford, 2015. "Psychology of Game Playing: Introduction to a Special Issue," Games, MDPI, vol. 6(4), pages 1-8, December.
    19. Ho, Teck-Hua, 1996. "Finite automata play repeated prisoner's dilemma with information processing costs," Journal of Economic Dynamics and Control, Elsevier, vol. 20(1-3), pages 173-207.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0204981. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.