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Learning in Networks Contexts: Experimental Results from Simulations

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Author Info

  • Eric Friedman

    () (Rutgers University)

  • Scott Shenker

    () (ICSI, Berkeley)

  • Amy Greenwald

    () (NYU)

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    Abstract

    This paper describes the results of simulation experiments performed on a suite of learning algorithms. We focus on games in {\em network contexts}. These are contexts in which (1) agents have very limited information about the game; users do not know their own (or any other agent's) payoff function, they merely observe the outcome of their play. (2) Play can be extremely asynchronous; players update their strategies at very different rates. There are many proposed learning algorithms in the literature. We choose a small sampling of such algorithms and use numerical simulation to explore the nature of asymptotic play. In particular, we explore the extent to which the asymptotic play depends on three factors, namely: limited information, asynchronous play, and the degree of responsiveness of the learning algorithm.

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    Bibliographic Info

    Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 199825.

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    Date of creation: 15 Oct 1998
    Date of revision:
    Handle: RePEc:rut:rutres:199825

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    Keywords: learning;

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    References

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    1. 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.
    2. T. Borgers & R. Sarin, 2010. "Learning Through Reinforcement and Replicator Dynamics," Levine's Working Paper Archive 380, David K. Levine.
    3. 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.
    4. Fudenberg, Drew & Levine, David, 1995. "Consistency and Cautious Fictitious Play," Scholarly Articles 3198694, Harvard University Department of Economics.
    5. Drew Fudenberg & David K. Levine, 1998. "Learning in Games," Levine's Working Paper Archive 2222, David K. Levine.
    6. D. B. Bernheim, 2010. "Rationalizable Strategic Behavior," Levine's Working Paper Archive 661465000000000381, David K. Levine.
    7. Eric J Friedman & Scott Schenker, 1997. "Learning and Implementation on the Internet," Levine's Working Paper Archive 595, David K. Levine.
    8. Friedman, Eric J., 1996. "Dynamics and Rationality in Ordered Externality Games," Games and Economic Behavior, Elsevier, vol. 16(1), pages 65-76, September.
    9. J. Watson, 2010. "A ‘Reputation’ Refinement without Equilibrium," Levine's Working Paper Archive 580, David K. Levine.
    10. Kalai, Ehud & Lehrer, Ehud, 1991. "Rational Learning Leads to Nash Equilibrium," Working Papers 91-18, C.V. Starr Center for Applied Economics, New York University.
    11. Pearce, David G, 1984. "Rationalizable Strategic Behavior and the Problem of Perfection," Econometrica, Econometric Society, vol. 52(4), pages 1029-50, July.
    12. Foster, Dean P. & Vohra, Rakesh V., 1997. "Calibrated Learning and Correlated Equilibrium," Games and Economic Behavior, Elsevier, vol. 21(1-2), pages 40-55, October.
    13. Drew Fudenberg & David K. Levine, 1997. "Conditional Universal Consistency," Levine's Working Paper Archive 471, David K. Levine.
    14. Fudenberg, Drew & Levine, David K, 1989. "Reputation and Equilibrium Selection in Games with a Patient Player," Econometrica, Econometric Society, vol. 57(4), pages 759-78, July.
    15. Sergiu Hart & Andreu Mas-Colell, 2000. "A Simple Adaptive Procedure Leading to Correlated Equilibrium," Econometrica, Econometric Society, vol. 68(5), pages 1127-1150, September.
    16. Foster, Dean P. & Vohra, Rakesh, 1999. "Regret in the On-Line Decision Problem," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 7-35, October.
    17. Rosenthal, Robert W., 1991. "A note on robustness of equilibria with respect to commitment opportunities," Games and Economic Behavior, Elsevier, vol. 3(2), pages 237-243, May.
    18. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945.
    19. Barry Sopher & Dilip Mookherjee, 1997. "Learning and Decision Costs in Experimental Constant Sum Games," Departmental Working Papers 199527, Rutgers University, Department of Economics.
    20. Nimrod Megiddo, 1979. "On Repeated Games with Incomplete Information Played by Non-Bayesian Players," Discussion Papers 373, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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    Cited by:
    1. Steffen Huck & Rajiv Sarin, 2000. "Players with Limited Memory," Econometric Society World Congress 2000 Contributed Papers 1645, Econometric Society.

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