IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2606.27653.html

Characterisation of reactive Nash equilibria in repeated additive games

Author

Listed:
  • Franziska Lesigang
  • Christian Hilbe
  • Nikoleta E. Glynatsi

Abstract

In this paper, we study reactive strategies in repeated additive games between two players with finitely many actions. Reactive strategies condition only on the opponent's previous action, making them one of the simplest ways players can respond to past interactions. Additive games include important models of cooperation, such as the donation game and games with a punishment option. We show that, for this class of games and strategies, the conditions for symmetric Nash equilibria reduce to a system of linear equalities and inequalities in the strategy parameters, allowing us to characterise all such equilibria. We establish a one-to-one correspondence between non-empty subsets S of the action set and equilibrium classes, which we call S-supporting equilibria. These are equilibria that use exactly the actions in S when playing against themselves. As a special case, we recover the well-known equalizer strategies as the equilibria supported on the entire action set. To assess which equilibrium classes are most evolutionarily relevant, we complement our analytical characterisation with simulations of social learning dynamics. We find that their prevalence is determined by two factors: how likely they are to be generated and how robust they are against invasion.

Suggested Citation

  • Franziska Lesigang & Christian Hilbe & Nikoleta E. Glynatsi, 2026. "Characterisation of reactive Nash equilibria in repeated additive games," Papers 2606.27653, arXiv.org.
  • Handle: RePEc:arx:papers:2606.27653
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2606.27653
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fudenberg, Drew & Imhof, Lorens A., 2006. "Imitation processes with small mutations," Journal of Economic Theory, Elsevier, vol. 131(1), pages 251-262, November.
    2. 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.
    3. Peter S. Park & Martin A. Nowak & Christian Hilbe, 2022. "Cooperation in alternating interactions with memory constraints," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Mailath, George J. & Samuelson, Larry, 2006. "Repeated Games and Reputations: Long-Run Relationships," OUP Catalogue, Oxford University Press, number 9780195300796.
    5. 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.
    6. Hilbe, Christian & Traulsen, Arne & Sigmund, Karl, 2015. "Partners or rivals? Strategies for the iterated prisoner's dilemma," Games and Economic Behavior, Elsevier, vol. 92(C), pages 41-52.
    7. Masahiko Ueda, 2022. "Controlling Conditional Expectations by Zero-Determinant Strategies," SN Operations Research Forum, Springer, vol. 3(3), pages 1-22, September.
    8. Luis A Martinez-Vaquero & José A Cuesta & Angel Sánchez, 2012. "Generosity Pays in the Presence of Direct Reciprocity: A Comprehensive Study of 2×2 Repeated Games," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-12, April.
    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. Maria Kleshnina & Christian Hilbe & Štěpán Šimsa & Krishnendu Chatterjee & Martin A. Nowak, 2023. "The effect of environmental information on evolution of cooperation in stochastic games," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Ueda, Masahiko, 2026. "Properties of zero-determinant strategies in multichannel games," Applied Mathematics and Computation, Elsevier, vol. 514(C).
    3. Peter S. Park & Martin A. Nowak & Christian Hilbe, 2022. "Cooperation in alternating interactions with memory constraints," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Christian Hilbe & Moshe Hoffman & Martin A. Nowak, 2015. "Cooperate without Looking in a Non-Repeated Game," Games, MDPI, vol. 6(4), pages 1-15, September.
    5. Konrad, Kai A. & Morath, Florian, 2020. "The Volunteer’s Dilemma in Finite Populations," CEPR Discussion Papers 15536, Centre for Economic Policy Research.
    6. Huang, Keke & Liu, Yishun & Zhang, Yichi & Yang, Chunhua & Wang, Zhen, 2018. "Understanding cooperative behavior of agents with heterogeneous perceptions in dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 234-240.
    7. 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.
    8. 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.
    9. Kurokawa, Shun & Lessard, Sabin, 2025. "The asymmetry between spite and altruism," Theoretical Population Biology, Elsevier, vol. 166(C), pages 107-115.
    10. Marta C. Couto & Saptarshi Pal, 2023. "Introspection Dynamics in Asymmetric Multiplayer Games," Dynamic Games and Applications, Springer, vol. 13(4), pages 1256-1285, December.
    11. 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).
    12. Sandholm, William H., 2012. "Stochastic imitative game dynamics with committed agents," Journal of Economic Theory, Elsevier, vol. 147(5), pages 2056-2071.
    13. Ueda, Masahiko, 2025. "On the implementation of zero-determinant strategies in repeated games," Applied Mathematics and Computation, Elsevier, vol. 489(C).
    14. Artem Baklanov, 2021. "Reactive Strategies: An Inch of Memory, a Mile of Equilibria," Games, MDPI, vol. 12(2), pages 1-28, May.
    15. Kai A. Konrad & Florian Morath, 2021. "The volunteer’s dilemma in finite populations," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1277-1290, September.
    16. Huang, Keke & Chen, Xiaofang & Yu, Zhaofei & Yang, Chunhua & Gui, Weihua, 2018. "Heterogeneous cooperative belief for social dilemma in multi-agent system," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 572-579.
    17. Zhang, Huanren, 2018. "Errors can increase cooperation in finite populations," Games and Economic Behavior, Elsevier, vol. 107(C), pages 203-219.
    18. Éloi Martin & Sabin Lessard, 2023. "Assortment by Group Founders Always Promotes the Evolution of Cooperation Under Global Selection But Can Oppose it Under Local Selection," Dynamic Games and Applications, Springer, vol. 13(4), pages 1194-1218, December.
    19. Allen, Benjamin & McAvoy, Alex, 2024. "The coalescent in finite populations with arbitrary, fixed structure," Theoretical Population Biology, Elsevier, vol. 158(C), pages 150-169.
    20. Zhou, Zhizhuo & Rong, Zhihai & Yang, Wen & Wu, Zhi-Xi, 2024. "Coevolution of extortion strategies with mixed imitation and aspiration learning dynamics in spatial Prisoner’s Dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2606.27653. 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: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    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.