IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpga/0110003.html
   My bibliography  Save this paper

Learning Under Little Information: An Experiment on Mutual Fate Control

Author

Listed:
  • Atanasios Mitropoulos

    (Otto-von-Guericke-University Magdeburg)

Abstract

Reinforcement learning has proved quite successful in predicting subjects' adjustment behaviour in repeatedly played simple games. However, reinforcement learning does not predict convergence to the efficient cell in the minimal information game of mutual fate control, while earlier psychologists' experiments show some tendency to convergence. Our rivalling learning rule, a modification of win-stay lose-change, does predict convergence. We perform an experiment using modern economic methodology and compare these two learning rules. Our results are unfavourable for both reinforcement learning as well as win- stay lose-change. The data rather support the view that subjects search by using patterns.

Suggested Citation

  • Atanasios Mitropoulos, 2001. "Learning Under Little Information: An Experiment on Mutual Fate Control," Game Theory and Information 0110003, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpga:0110003
    Note: Type of Document - Acrobat PDF; prepared on IBM PC - MS-Word; to print on HP A4 size; pages: 33; figures: included. revised version appeared in the Journal of Economic Psychology 22 (2001) 523-557
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/game/papers/0110/0110003.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huck, Steffen & Normann, Hans-Theo & Oechssler, Jorg, 2000. "Does information about competitors' actions increase or decrease competition in experimental oligopoly markets?," International Journal of Industrial Organization, Elsevier, vol. 18(1), pages 39-57, January.
    2. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    3. 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.
    4. Mookherjee Dilip & Sopher Barry, 1994. "Learning Behavior in an Experimental Matching Pennies Game," Games and Economic Behavior, Elsevier, vol. 7(1), pages 62-91, July.
    5. Kalai, Ehud & Lehrer, Ehud, 1995. "Subjective games and equilibria," Games and Economic Behavior, Elsevier, vol. 8(1), pages 123-163.
    6. Rosemarie Nagel & Nicolaas J. Vriend, 1999. "An experimental study of adaptive behavior in an oligopolistic market game," Journal of Evolutionary Economics, Springer, vol. 9(1), pages 27-65.
    7. Hon-Snir, Shlomit & Monderer, Dov & Sela, Aner, 1998. "A Learning Approach to Auctions," Journal of Economic Theory, Elsevier, vol. 82(1), pages 65-88, September.
    8. A. Roth & I. Er’ev, 2010. "Learning in Extensive Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Run," Levine's Working Paper Archive 387, David K. Levine.
    9. Crawford, Vincent P, 1995. "Adaptive Dynamics in Coordination Games," Econometrica, Econometric Society, vol. 63(1), pages 103-143, January.
    10. Huck, Steffen & Normann, Hans-Theo & Oechssler, Jorg, 1999. "Learning in Cournot Oligopoly--An Experiment," Economic Journal, Royal Economic Society, vol. 109(454), pages 80-95, March.
    11. 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.
    12. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    13. Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
    14. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    15. 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.
    16. Milgrom, Paul & Roberts, John, 1991. "Adaptive and sophisticated learning in normal form games," Games and Economic Behavior, Elsevier, vol. 3(1), pages 82-100, February.
    17. Smith, Vernon L, 1985. "Experimental Economics: Reply," American Economic Review, American Economic Association, vol. 75(1), pages 264-272, March.
    18. Nick Feltovich & John Duffy, 1999. "Does observation of others affect learning in strategic environments? An experimental study," International Journal of Game Theory, Springer;Game Theory Society, vol. 28(1), pages 131-152.
    19. Erev, Ido & Rapoport, Amnon, 1998. "Coordination, "Magic," and Reinforcement Learning in a Market Entry Game," Games and Economic Behavior, Elsevier, vol. 23(2), pages 146-175, May.
    20. Conlisk, John, 1993. "Adaptive tactics in games : Further solutions to the Crawford puzzle," Journal of Economic Behavior & Organization, Elsevier, vol. 22(1), pages 51-68, September.
    21. 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.
    22. Milgrom, Paul & Roberts, John, 1990. "Rationalizability, Learning, and Equilibrium in Games with Strategic Complementarities," Econometrica, Econometric Society, vol. 58(6), pages 1255-1277, November.
    23. John G. Cross, 1973. "A Stochastic Learning Model of Economic Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(2), pages 239-266.
    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. Dekel, Eddie & Fudenberg, Drew & Levine, David K., 2004. "Learning to play Bayesian games," Games and Economic Behavior, Elsevier, vol. 46(2), pages 282-303, February.
    2. Mitropoulos, Atanasios, 2003. "An experiment on the value of structural information in a 2 x 2 repeated game," Economics Letters, Elsevier, vol. 78(1), pages 27-32, January.
    3. Andreas Nicklisch, 2011. "Learning strategic environments: an experimental study of strategy formation and transfer," Theory and Decision, Springer, vol. 71(4), pages 539-558, October.
    4. Andreas Nicklisch, 2006. "Perceiving strategic environments: An experimental study of learning under minimal information," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2006_17, Max Planck Institute for Research on Collective Goods.
    5. Atanasios Mitropoulos, 2001. "On the Measurement of the Predictive Success of Learning Theories in Repeated Games," Experimental 0110001, University Library of Munich, Germany.
    6. Andreas Nicklisch, 2004. "Perceiving strategic environments -An experimental study of strategy formation and transfer-," Papers on Strategic Interaction 2004-26, Max Planck Institute of Economics, Strategic Interaction Group.

    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. Mitropoulos, Atanasios, 2001. "Learning under minimal information: An experiment on mutual fate control," Journal of Economic Psychology, Elsevier, vol. 22(4), pages 523-557, August.
    2. Teck H Ho & Colin Camerer & Juin-Kuan Chong, 2003. "Functional EWA: A one-parameter theory of learning in games," Levine's Working Paper Archive 506439000000000514, David K. Levine.
    3. Ed Hopkins, 2002. "Two Competing Models of How People Learn in Games," Econometrica, Econometric Society, vol. 70(6), pages 2141-2166, November.
    4. Battalio,R. & Samuelson,L. & Huyck,J. van, 1998. "Risk dominance, payoff dominance and probabilistic choice learning," Working papers 2, Wisconsin Madison - Social Systems.
    5. Ho, Teck H. & Camerer, Colin F. & Chong, Juin-Kuan, 2007. "Self-tuning experience weighted attraction learning in games," Journal of Economic Theory, Elsevier, vol. 133(1), pages 177-198, March.
    6. Asim Ansari & Ricardo Montoya & Oded Netzer, 2012. "Dynamic learning in behavioral games: A hidden Markov mixture of experts approach," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 475-503, December.
    7. Andreas Nicklisch, 2006. "Perceiving strategic environments: An experimental study of learning under minimal information," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2006_17, Max Planck Institute for Research on Collective Goods.
    8. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011, Elsevier.
    9. 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.
    10. Andreas Nicklisch, 2011. "Learning strategic environments: an experimental study of strategy formation and transfer," Theory and Decision, Springer, vol. 71(4), pages 539-558, October.
    11. 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.
    12. Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
    13. Camerer, Colin F. & Ho, Teck-Hua & Chong, Juin-Kuan, 2002. "Sophisticated Experience-Weighted Attraction Learning and Strategic Teaching in Repeated Games," Journal of Economic Theory, Elsevier, vol. 104(1), pages 137-188, May.
    14. Pangallo, Marco & Sanders, James B.T. & Galla, Tobias & Farmer, J. Doyne, 2022. "Towards a taxonomy of learning dynamics in 2 × 2 games," Games and Economic Behavior, Elsevier, vol. 132(C), pages 1-21.
    15. George R. Neumann & Nathan E. Savin, 2000. "Learning and Communication in Sender-Receiver Games: An Econometric Investigation," Econometric Society World Congress 2000 Contributed Papers 1852, Econometric Society.
    16. Teck H. Ho & Xin Wang & Colin F. Camerer, 2008. "Individual Differences in EWA Learning with Partial Payoff Information," Economic Journal, Royal Economic Society, vol. 118(525), pages 37-59, January.
    17. Terracol, Antoine & Vaksmann, Jonathan, 2009. "Dumbing down rational players: Learning and teaching in an experimental game," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 54-71, May.
    18. Erhao Xie, 2019. "Monetary Payoff and Utility Function in Adaptive Learning Models," Staff Working Papers 19-50, Bank of Canada.
    19. DeJong, D.V. & Blume, A. & Neumann, G., 1998. "Learning in Sender-Receiver Games," Other publications TiSEM 4a8b4f46-f30b-4ad2-bb0c-1, Tilburg University, School of Economics and Management.
    20. 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.

    More about this item

    Keywords

    mutual fate control; learning; coordination; experimental economics; coordination failure;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior

    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:wpa:wuwpga:0110003. 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: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    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.