IDEAS home Printed from https://ideas.repec.org/p/ssb/dispap/282.html
   My bibliography  Save this paper

Networking Strategy: Cooperate Today in Order to Meet a Cooperator Tomorrow

Author

Abstract

This paper explains why people might cooperate playing an infinitely recurring prisoners' dilemma in which they change their partner in every period. After two people have played the prisoners' dilemma there is a possibility for networking. Then, two cooperators who played against each other exchange information about cooperators that they have met in previous periods. In the next period, they use this information in order to increase their probability of matching with a cooperator. Whether it is payoff maximizing to cooperate, given that all cooperators network, depends on the share of cooperators in the society. People learn their optimal strategy in a learning process which is represented by a payoff monotonic dynamic. The evolutionary analysis shows that there exist two stable states: One state in which a large share of the people in the society cooperate, and another state in which nobody cooperates.

Suggested Citation

  • Mari Rege, 2000. "Networking Strategy: Cooperate Today in Order to Meet a Cooperator Tomorrow," Discussion Papers 282, Statistics Norway, Research Department.
    • Handle: RePEc:ssb:dispap:282
    as

    Download full text from publisher

    File URL: https://www.ssb.no/a/publikasjoner/pdf/DP/dp282.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. Harrington, Joseph Jr., 1995. "Cooperation in a one-shot Prisoners' Dilemma," Games and Economic Behavior, Elsevier, vol. 8(2), pages 364-377.
    3. Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
    4. Glenn Ellison, 1994. "Cooperation in the Prisoner's Dilemma with Anonymous Random Matching," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(3), pages 567-588.
    5. Schlag, Karl H., 1998. "Why Imitate, and If So, How?, : A Boundedly Rational Approach to Multi-armed Bandits," Journal of Economic Theory, Elsevier, vol. 78(1), pages 130-156, January.
    6. Okuno-Fujiwara Masahiro & Postlewaite Andrew, 1995. "Social Norms and Random Matching Games," Games and Economic Behavior, Elsevier, vol. 9(1), pages 79-109, April.
    7. Schlag, Karl H., 1998. "Why Imitate, and If So, How?, : A Boundedly Rational Approach to Multi-armed Bandits," Journal of Economic Theory, Elsevier, vol. 78(1), pages 130-156, January.
    8. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, December.
    9. Michihiro Kandori, 1992. "Social Norms and Community Enforcement," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(1), pages 63-80.
    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. Mohlin, Erik & Östling, Robert & Wang, Joseph Tao-yi, 2020. "Learning by similarity-weighted imitation in winner-takes-all games," Games and Economic Behavior, Elsevier, vol. 120(C), pages 225-245.
    2. Weibull, Jorgen W., 1998. "Evolution, rationality and equilibrium in games," European Economic Review, Elsevier, vol. 42(3-5), pages 641-649, May.
    3. Francesco Squintani, 1999. "Moral Hazard," Discussion Papers 1269, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    4. Ed Hopkins & Robert M. Seymour, 2002. "The Stability of Price Dispersion under Seller and Consumer Learning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1157-1190, November.
    5. Ratul Lahkar & Sayan Mukherjee & Souvik Roy, 2022. "A Deterministic Approximation Approach to the Continuum Logit Dynamic with an Application to Supermodular Games," Working Papers 79, Ashoka University, Department of Economics.
    6. Mertikopoulos, Panayotis & Sandholm, William H., 2018. "Riemannian game dynamics," Journal of Economic Theory, Elsevier, vol. 177(C), pages 315-364.
    7. Ulrich Berger, 2003. "A general model of best response adaptation," Game Theory and Information 0303008, University Library of Munich, Germany.
    8. Balkenborg, Dieter & Schlag, Karl H., 2007. "On the evolutionary selection of sets of Nash equilibria," Journal of Economic Theory, Elsevier, vol. 133(1), pages 295-315, March.
    9. Tassos Patokos, 2014. "Introducing Disappointment Dynamics and Comparing Behaviors in Evolutionary Games: Some Simulation Results," Games, MDPI, vol. 5(1), pages 1-25, January.
    10. Levine, David K. & Pesendorfer, Wolfgang, 2007. "The evolution of cooperation through imitation," Games and Economic Behavior, Elsevier, vol. 58(2), pages 293-315, February.
    11. Lahkar, Ratul & Sandholm, William H., 2008. "The projection dynamic and the geometry of population games," Games and Economic Behavior, Elsevier, vol. 64(2), pages 565-590, November.
    12. Reinoud Joosten, 2009. "Paul Samuelson's critique and equilibrium concepts in evolutionary game theory," Papers on Economics and Evolution 2009-16, Philipps University Marburg, Department of Geography.
    13. Erik Mohlin & Robert Ostling & Joseph Tao-yi Wang, 2014. "Learning by Imitation in Games: Theory, Field, and Laboratory," Economics Series Working Papers 734, University of Oxford, Department of Economics.
    14. repec:ehu:ikerla:9171 is not listed on IDEAS
    15. Waters, George A., 2009. "Chaos in the cobweb model with a new learning dynamic," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1201-1216, June.
    16. Sandholm,W.H., 2003. "Excess payoff dynamics, potential dynamics, and stable games," Working papers 5, Wisconsin Madison - Social Systems.
    17. Antonio Morales, 2005. "On the Role of the Group Composition for Achieving Optimality," Annals of Operations Research, Springer, vol. 137(1), pages 387-397, July.
    18. Alessandro Lizzeri & Marciano Siniscalchi, 2008. "Parental Guidance and Supervised Learning," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(3), pages 1161-1195.
    19. Michel BenaÔm & J–rgen W. Weibull, 2003. "Deterministic Approximation of Stochastic Evolution in Games," Econometrica, Econometric Society, vol. 71(3), pages 873-903, May.
    20. Fudenberg, Drew & Imhof, Lorens A., 2006. "Imitation processes with small mutations," Journal of Economic Theory, Elsevier, vol. 131(1), pages 251-262, November.
    21. Apesteguia, Jose & Huck, Steffen & Oechssler, Jorg, 2007. "Imitation--theory and experimental evidence," Journal of Economic Theory, Elsevier, vol. 136(1), pages 217-235, September.

    More about this item

    Keywords

    cooperation; evolution; networking; prisoners' dilemma;
    All these keywords.

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory

    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:ssb:dispap:282. 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: L Maasø (email available below). General contact details of provider: https://edirc.repec.org/data/ssbgvno.html .

    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.