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An Experimental Investigation of Optimal Learning in Coordination Games

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  • Andreas Blume
  • Uri Gneezy

Abstract

This paper presents an experimental investigation of optimal learning in repeated coordination games. We find evidence for such learning when we limit both the cognitive demands on players and the information available to them. We also find that uniqueness of the optimal strategy is no guarantee for it to be used. Optimal learning can be impeded by both irrelevant information and the complexity of the coordination task. ZUSAMMENFASSUNG - (Eine experimentelle Untersuchung des optimalen Lernens in Koordinationsspielen) In diesem Beitrag wird eine experimentelle Untersuchung des optimalen Lernens in wiederholten Koordinationsspielen vorgestellt. Derartiges Lernen wird beobachtet, wenn kognitive Anforderungen an die Spieler und die ihnen zur Verfügung stehende Information begrenzt sind. Es zeigt sich aber auch, daß die Einzigartigkeit der optimalen Strategie keine Garantie dafür ist, daß sie angewendet wird. Optimales Lernen kann sowohl durch irrelevante Informationen als auch durch die Komplexität der Koordinationsaufgabe behindert werden.

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  • Andreas Blume & Uri Gneezy, 1998. "An Experimental Investigation of Optimal Learning in Coordination Games," CIG Working Papers FS IV 98-12, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
    • Handle: RePEc:wzb:wzebiv:fsiv98-12
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    1. John C. Harsanyi & Reinhard Selten, 1988. "A General Theory of Equilibrium Selection in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262582384, April.
    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. Bacharach, Michael & Bernasconi, Michele, 1997. "The Variable Frame Theory of Focal Points: An Experimental Study," Games and Economic Behavior, Elsevier, vol. 19(1), pages 1-45, April.
    6. Blume, Andreas, et al, 1998. "Experimental Evidence on the Evolution of Meaning of Messages in Sender-Receiver Games," American Economic Review, American Economic Association, vol. 88(5), pages 1323-1340, December.
    7. Sugden, Robert, 1995. "A Theory of Focal Points," Economic Journal, Royal Economic Society, vol. 105(430), pages 533-550, May.
    8. Crawford, Vincent, 1998. "A Survey of Experiments on Communication via Cheap Talk," Journal of Economic Theory, Elsevier, vol. 78(2), pages 286-298, February.
    9. 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.
    10. Crawford, Vincent P & Haller, Hans, 1990. "Learning How to Cooperate: Optimal Play in Repeated Coordination Games," Econometrica, Econometric Society, vol. 58(3), pages 571-595, May.
    11. 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.
    12. Roth, Alvin E & Murnighan, J Keith, 1982. "The Role of Information in Bargaining: An Experimental Study," Econometrica, Econometric Society, vol. 50(5), pages 1123-1142, September.
    13. Rubinstein, Ariel, 1996. "Why Are Certain Properties of Binary Relations Relatively More Common in Natural Language?," Econometrica, Econometric Society, vol. 64(2), pages 343-355, March.
    14. Mehta, Judith & Starmer, Chris & Sugden, Robert, 1994. "The Nature of Salience: An Experimental Investigation of Pure Coordination Games," American Economic Review, American Economic Association, vol. 84(3), pages 658-673, June.
    15. 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.
    16. J. Robinson, 1969. "An Iterative Method of Solving a Game," Levine's Working Paper Archive 422, David K. Levine.
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