IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0327131.html

Commitment & cooperation in social dilemmas with diverse individual preferences: An agent-based modeling approach

Author

Listed:
  • Zheng Jiang
  • Luzhan Yuan
  • Wei Wang
  • Gaowei Zhang
  • Yi Wang

Abstract

Social dilemmas often arise when the need for cooperation conflicts with individuals’ incentives to act in self-interest, potentially undermining collective well-being. Prior literature shows that some mechanisms, e.g., commitment, could give rise to cooperation. However, participants’ diverse propensities to cooperate may limit such mechanisms’ effectiveness. Thus, we bring individual differences in their propensities to cooperate into the reasoning of long-term social dynamics of cooperation through an agent-based modeling (ABM) approach. Our results suggest that commitment may still guarantee cooperation when individuals have different propensities to cooperate but have weaker effects, and the setups of commitment are also important. Our study highlights the importance of integrating individual preferences in analyzing collective dynamics of a population consisting of individuals of heterogeneous characteristics, thus offering implications to facilitate cooperation in real-world online social production. The model and its implementation also form the foundation for supporting decision-makers in forming decisions of facilitating cooperation via commitment mechanisms.

Suggested Citation

  • Zheng Jiang & Luzhan Yuan & Wei Wang & Gaowei Zhang & Yi Wang, 2025. "Commitment & cooperation in social dilemmas with diverse individual preferences: An agent-based modeling approach," PLOS ONE, Public Library of Science, vol. 20(7), pages 1-25, July.
    • Handle: RePEc:plo:pone00:0327131
    DOI: 10.1371/journal.pone.0327131
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0327131
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0327131&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0327131?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. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. Chrysanthos Dellarocas, 2005. "Reputation Mechanism Design in Online Trading Environments with Pure Moral Hazard," Information Systems Research, INFORMS, vol. 16(2), pages 209-230, June.
    3. 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.
    4. Herbert Gintis, 2014. "The Bounds of Reason: Game Theory and the Unification of the Behavioral Sciences," Economics Books, Princeton University Press, edition 1, number 10248, 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. Galbiati, Marco & Soramäki, Kimmo, 2011. "An agent-based model of payment systems," Journal of Economic Dynamics and Control, Elsevier, vol. 35(6), pages 859-875, June.
    2. Schipper, Burkhard C., 2021. "Discovery and equilibrium in games with unawareness," Journal of Economic Theory, Elsevier, vol. 198(C).
    3. Mathieu Faure & Gregory Roth, 2010. "Stochastic Approximations of Set-Valued Dynamical Systems: Convergence with Positive Probability to an Attractor," Mathematics of Operations Research, INFORMS, vol. 35(3), pages 624-640, August.
    4. Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 203, Economics Division, School of Social Sciences, University of Southampton.
    5. Christian Ewerhart, 2020. "Ordinal potentials in smooth games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 70(4), pages 1069-1100, November.
    6. Benaïm, Michel & Hofbauer, Josef & Hopkins, Ed, 2009. "Learning in games with unstable equilibria," Journal of Economic Theory, Elsevier, vol. 144(4), pages 1694-1709, July.
    7. Saori Iwanaga & Akira Namatame, 2015. "Hub Agents Determine Collective Behavior," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 165-181.
    8. Erhao Xie, 2019. "Monetary Payoff and Utility Function in Adaptive Learning Models," Staff Working Papers 19-50, Bank of Canada.
    9. Jacob W. Crandall & Mayada Oudah & Tennom & Fatimah Ishowo-Oloko & Sherief Abdallah & Jean-François Bonnefon & Manuel Cebrian & Azim Shariff & Michael A. Goodrich & Iyad Rahwan, 2018. "Cooperating with machines," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
      • Abdallah, Sherief & Bonnefon, Jean-François & Cebrian, Manuel & Crandall, Jacob W. & Ishowo-Oloko, Fatimah & Oudah, Mayada & Rahwan, Iyad & Shariff, Azim & Tennom,, 2017. "Cooperating with Machines," TSE Working Papers 17-806, Toulouse School of Economics (TSE).
      • Abdallah, Sherief & Bonnefon, Jean-François & Cebrian, Manuel & Crandall, Jacob W. & Ishowo-Oloko, Fatimah & Oudah, Mayada & Rahwan, Iyad & Shariff, Azim & Tennom,, 2017. "Cooperating with Machines," IAST Working Papers 17-68, Institute for Advanced Study in Toulouse (IAST).
    10. B Kelsey Jack, 2009. "Auctioning Conservation Contracts in Indonesia - Participant Learning in Multiple Trial Rounds," CID Working Papers 35, Center for International Development at Harvard University.
    11. 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.
    12. William L. Cooper & Tito Homem-de-Mello & Anton J. Kleywegt, 2015. "Learning and Pricing with Models That Do Not Explicitly Incorporate Competition," Operations Research, INFORMS, vol. 63(1), pages 86-103, February.
    13. repec:osf:osfxxx:9vm5t_v1 is not listed on IDEAS
    14. Cho, In-Koo, 2005. "Introduction to learning and bounded rationality," Journal of Economic Theory, Elsevier, vol. 124(2), pages 127-128, October.
    15. Ball, Richard, 2017. "Violations of monotonicity in evolutionary models with sample-based beliefs," Economics Letters, Elsevier, vol. 152(C), pages 100-104.
    16. Arcaute, E. & Dyagilev, K. & Johari, R. & Mannor, S., 2013. "Dynamics in tree formation games," Games and Economic Behavior, Elsevier, vol. 79(C), pages 1-29.
    17. Jesper Breinbjerg & Alexander Sebald & Lars Peter Østerdal, 2016. "Strategic behavior and social outcomes in a bottleneck queue: experimental evidence," Review of Economic Design, Springer;Society for Economic Design, vol. 20(3), pages 207-236, September.
    18. Sandholm,W.H., 2003. "Excess payoff dynamics, potential dynamics, and stable games," Working papers 5, Wisconsin Madison - Social Systems.
    19. repec:plo:pone00:0128121 is not listed on IDEAS
    20. Yoo, Seung Han, 2014. "Learning a population distribution," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 188-201.
    21. Bin Ye & Jingjing Jiang & Lixin Miao & Ji Li & Yang Peng, 2015. "Innovative Carbon Allowance Allocation Policy for the Shenzhen Emission Trading Scheme in China," Sustainability, MDPI, vol. 8(1), pages 1-23, December.
    22. Vinil T Chackochan & Vittorio Sanguineti, 2019. "Incomplete information about the partner affects the development of collaborative strategies in joint action," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-23, December.

    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:pone00:0327131. 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.