IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v8y2017i1d10.1038_ncomms15147.html

Payoff information hampers the evolution of cooperation

Author

Listed:
  • Steffen Huck

    (WZB
    University College London)

  • Johannes Leutgeb

    (WZB)

  • Ryan Oprea

    (University of California, Santa Barbara)

Abstract

Human cooperation has been explained through rationality as well as heuristics-based models. Both model classes share the feature that knowledge of payoff functions is weakly beneficial for the emergence of cooperation. Here, we present experimental evidence to the contrary. We let human subjects interact in a competitive environment and find that, in the long run, access to information about own payoffs leads to less cooperative behaviour. In the short run subjects use naive learning heuristics that get replaced by better adapted heuristics in the long run. With more payoff information subjects are less likely to switch to pro-cooperative heuristics. The results call for the development of two-tier models for the evolution of cooperation.

Suggested Citation

  • Steffen Huck & Johannes Leutgeb & Ryan Oprea, 2017. "Payoff information hampers the evolution of cooperation," Nature Communications, Nature, vol. 8(1), pages 1-5, August.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15147
    DOI: 10.1038/ncomms15147
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms15147
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms15147?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
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dimitri Dubois & Stefano Farolfi & Phu Nguyen-Van & Juliette Rouchier, 2018. "Information sharing is not always the right option when it comes to CPR extraction management: experimental findings," Working Papers of BETA 2018-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    2. Xiaomeng Ding & Simon Weidenholzer & Boyu Zhang, 2025. "Evolving Rules: Imitation and Best Response Learning in Cournot Oligopoly," Papers 2511.09839, arXiv.org.
    3. Backhaus, Teresa & Huck, Steffen & Leutgeb, Johannes & Oprea, Ryan, 2023. "Learning through period and physical time," Games and Economic Behavior, Elsevier, vol. 141(C), pages 21-29.
    4. Collins, Sean M. & James, Duncan & Servátka, Maroš & Vadovič, Radovan, 2020. "Attainment of Equilibrium: Marshallian Path Adjustment and Buyer Determinism," MPRA Paper 104103, University Library of Munich, Germany.
    5. Collins, Sean M. & James, Duncan & Servátka, Maroš & Vadovič, Radovan, 2021. "Attainment of equilibrium via Marshallian path adjustment: Queueing and buyer determinism," Games and Economic Behavior, Elsevier, vol. 125(C), pages 94-106.
    6. Jiang, Zhi-Qiang & Wang, Peng & Ma, Jun-Chao & Zhu, Peican & Han, Zhen & Podobnik, Boris & Stanley, H. Eugene & Zhou, Wei-Xing & Alfaro-Bittner, Karin & Boccaletti, Stefano, 2023. "Unraveling the effects of network, direct and indirect reciprocity in online societies," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    7. Guan, Junbiao & Wang, Kaihua, 2020. "Cooperative evolution in pedestrian room evacuation considering different individual behaviors," Applied Mathematics and Computation, Elsevier, vol. 369(C).

    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:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15147. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.