IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v29y2007i3p421-421.html
   My bibliography  Save this article

Individual and Social Learning

Author

Listed:
  • Nobuyuki Hanaki

Abstract

We use adaptive models to understand the dynamics that lead to efficient and fair outcomes in a repeated Battle of the Sexes game. Human subjects appear to easily recognize the possibility of a coordinated alternation of actions as a mean to generate an efficient and fair outcome. Yet such typical learning models as Fictitious Play and Reinforcement Learning have found it hard to replicate this particular result. We develop a model that not only uses individual learning but also the “social learning” that operates through evolutionary selection. We find that the efficient and fair outcome emerges relatively quickly in our model. Copyright Springer Science+Business Media, Inc. 2005
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Nobuyuki Hanaki, 2007. "Individual and Social Learning," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 421-421, May.
    • Handle: RePEc:kap:compec:v:29:y:2007:i:3:p:421-421
    DOI: 10.1007/s10614-006-9055-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-006-9055-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10614-006-9055-1?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hanaki, Nobuyuki & Sethi, Rajiv & Erev, Ido & Peterhansl, Alexander, 2005. "Learning strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 523-542, April.
    2. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    3. Mookherjee, Dilip & Sopher, Barry, 1997. "Learning and Decision Costs in Experimental Constant Sum Games," Games and Economic Behavior, Elsevier, vol. 19(1), pages 97-132, April.
    4. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    5. Charness, Gary & Rabin, Matthew, 2002. "Understanding Social Preferences with Simple Tests," Department of Economics, Working Paper Series qt3d04q5sm, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    6. Cheung, Yin-Wong & Friedman, Daniel, 1997. "Individual Learning in Normal Form Games: Some Laboratory Results," Games and Economic Behavior, Elsevier, vol. 19(1), pages 46-76, April.
    7. Martin J. Osborne & Ariel Rubinstein, 1994. "A Course in Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262650401, April.
    8. Miller, John H., 1996. "The coevolution of automata in the repeated Prisoner's Dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 29(1), pages 87-112, January.
    9. Rabin, Matthew, 1993. "Incorporating Fairness into Game Theory and Economics," American Economic Review, American Economic Association, vol. 83(5), pages 1281-1302, December.
    10. Charness, Gary & Rabin, Matthew, 2001. "Understanding Social Preferences with Simple Tests," Department of Economics, Working Paper Series qt4qz9k8vg, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    11. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    12. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, April.
    13. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, April.
    14. Gary Charness & Matthew Rabin, 2002. "Understanding Social Preferences with Simple Tests," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(3), pages 817-869.
    15. Arifovic, Jasmina & McKelvey, Richard D. & Pevnitskaya, Svetlana, 2006. "An initial implementation of the Turing tournament to learning in repeated two-person games," Games and Economic Behavior, Elsevier, vol. 57(1), pages 93-122, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Cynthia Chen & Jason Chen, 2009. "What is responsible for the response lag of a significant change in discretionary time use: the built environment, family and social obligations, temporal constraints, or a psychological delay factor?," Transportation, Springer, vol. 36(1), pages 27-46, January.
    2. Shu-Heng Chan & Shu G. Wang, 2010. "Emergent Complexity in Agent-Based Computational Economics," ASSRU Discussion Papers 1017, ASSRU - Algorithmic Social Science Research Unit.
    3. Zhang, Huanren, 2018. "Errors can increase cooperation in finite populations," Games and Economic Behavior, Elsevier, vol. 107(C), pages 203-219.
    4. Shu‐Heng Chen & Shu G. Wang, 2011. "Emergent Complexity In Agent‐Based Computational Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(3), pages 527-546, July.
    5. Liangjie Zhao & Wenqi Duan, 2014. "Simulating the Evolution of Market Shares: The Effects of Customer Learning and Local Network Externalities," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 53-70, January.

    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. Hanaki, Nobuyuki & Sethi, Rajiv & Erev, Ido & Peterhansl, Alexander, 2005. "Learning strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 523-542, April.
    2. James Andreoni & Marco Castillo & Ragan Petrie, 2009. "Revealing Preferences for Fairness in Ultimatum Bargaining," Korean Economic Review, Korean Economic Association, vol. 25, pages 35-63.
    3. Hanaki, Nobuyuki & Ishikawa, Ryuichiro & Akiyama, Eizo, 2009. "Learning games," Journal of Economic Dynamics and Control, Elsevier, vol. 33(10), pages 1739-1756, October.
    4. Andreozzi, Luciano, 2013. "Learning to be fair," Journal of Economic Behavior & Organization, Elsevier, vol. 90(C), pages 181-195.
    5. Camerer, Colin F. & Ho, Teck-Hua, 2015. "Behavioral Game Theory Experiments and Modeling," Handbook of Game Theory with Economic Applications,, Elsevier.
    6. Cason, Timothy N. & Saijo, Tatsuyoshi & Yamato, Takehiko & Yokotani, Konomu, 2004. "Non-excludable public good experiments," Games and Economic Behavior, Elsevier, vol. 49(1), pages 81-102, October.
    7. Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
    8. Mengel, Friederike & Orlandi, Ludovica & Weidenholzer, Simon, 2022. "Match length realization and cooperation in indefinitely repeated games," Journal of Economic Theory, Elsevier, vol. 200(C).
    9. Colin F. Camerer & Ernst Fehr, "undated". "Measuring Social Norms and Preferences using Experimental Games: A Guide for Social Scientists," IEW - Working Papers 097, Institute for Empirical Research in Economics - University of Zurich.
    10. V. P. Crawford, 2014. "Boundedly rational versus optimization-based models of strategic thinking and learning in games," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 5.
    11. Erlei, Mathias, 2008. "Heterogeneous social preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 65(3-4), pages 436-457, March.
    12. Tatsuyoshi Saijo & Takehiko Yamato & Konomu Yokotani, 2003. "Non-Excludable Public Good Experiments revised October 2003, forthcoming in Games and Economic Behavior," Discussion papers 03011, Research Institute of Economy, Trade and Industry (RIETI).
    13. Erhao Xie, 2019. "Monetary Payoff and Utility Function in Adaptive Learning Models," Staff Working Papers 19-50, Bank of Canada.
    14. Jacob K. Goeree & Charles A. Holt, 2001. "Ten Little Treasures of Game Theory and Ten Intuitive Contradictions," American Economic Review, American Economic Association, vol. 91(5), pages 1402-1422, December.
    15. Olivier Armantier, 2006. "Do Wealth Differences Affect Fairness Considerations?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 391-429, May.
    16. Xie, Erhao, 2021. "Empirical properties and identification of adaptive learning models in behavioral game theory," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 798-821.
    17. Aina, Chiara & Battigalli, Pierpaolo & Gamba, Astrid, 2020. "Frustration and anger in the Ultimatum Game: An experiment," Games and Economic Behavior, Elsevier, vol. 122(C), pages 150-167.
    18. Charness, Gary & Naef, Michael & Sontuoso, Alessandro, 2019. "Opportunistic conformism," Journal of Economic Theory, Elsevier, vol. 180(C), pages 100-134.
    19. Charness, Gary & Dufwenberg, Martin, 2003. "Promises & Partnership," Research Papers in Economics 2003:3, Stockholm University, Department of Economics.
    20. Dmitry Shapiro, 2009. "The role of utility interdependence in public good experiments," International Journal of Game Theory, Springer;Game Theory Society, vol. 38(1), pages 81-106, March.

    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:kap:compec:v:29:y:2007:i:3:p:421-421. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.