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Rage Against the Machines: How Subjects Learn to Play Against Computers

  • Dürsch, Peter
  • Kolb, Albert
  • Oechssler, Jörg
  • Schipper, Burkhard C.

We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious play, imitation, reinforcement learning, and a trial & error process. We test whether subjects try to influence those algorithms to their advantage in a forward-looking way (strategic teaching). We find that strategic teaching occurs frequently and that all learning algorithms are subject to exploitation with the notable exception of imitation. The experiment was conducted, both, on the internet and in the usual laboratory setting. We find some systematic differences, which however can be traced to the different incentives structures rather than the experimental environment.

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Paper provided by Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich in its series Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems with number 63.

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Date of creation: Oct 2005
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Handle: RePEc:trf:wpaper:63
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  1. Mathias Drehmann & Joerg Oechssler & Andreas Roider, 2002. "Herding and Contrarian Behavior in Financial Markets - An Internet Experiment," Finance 0210005, EconWPA.
  2. Offerman, T.J.S. & Potters, J.J.M. & Sonnemans, J., 2002. "Imitation and belief learning in an oligopoly experiment," Other publications TiSEM a6a771c5-31ba-4193-8f76-a, Tilburg University, School of Economics and Management.
  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 848-81, September.
  4. Shachat, Jason & Swarthout, J. Todd, 2012. "Learning about learning in games through experimental control of strategic interdependence," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 383-402.
  5. Fernando Vega Redondo, 1996. "The evolution of walrasian behavior," Working Papers. Serie AD 1996-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  6. Steffen Huck & Hans-Theo Normann & Joerg Oechssler, 1998. "Through Trial & Error to Collusion," Game Theory and Information 9811004, EconWPA, revised 24 Nov 1998.
  7. Jose Alpesteguia & Steffen Huck & Jörg Oechssler, 2003. "Imitation - Theory and Experimental Evidence," CESifo Working Paper Series 1049, CESifo Group Munich.
  8. Alos-Ferrer, Carlos, 2004. "Cournot versus Walras in dynamic oligopolies with memory," International Journal of Industrial Organization, Elsevier, vol. 22(2), pages 193-217, February.
  9. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
  10. 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.
  11. Glen Ellison, 2010. "Learning from Personal Experience: One Rational Guy and the Justification of Myopia," Levine's Working Paper Archive 413, David K. Levine.
  12. J.-F. Laslier & R. Topol & B. Walliser, 1999. "A behavioral learning process in games," THEMA Working Papers 99-03, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  13. Huck, Steffen & Normann, Hans-Theo & Oechssler, Jorg, 2004. "Two are few and four are many: number effects in experimental oligopolies," Journal of Economic Behavior & Organization, Elsevier, vol. 53(4), pages 435-446, April.
  14. Burkhard Schipper, 2002. "Imitators and Optimizers in Cournot Oligopoly," Bonn Econ Discussion Papers bgse29_2002, University of Bonn, Germany.
  15. Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 0203, Economics Division, School of Social Sciences, University of Southampton.
  16. Kirchkamp, Oliver & Nagel, Rosemarie, 2005. "Learning and cooperation in network experiments," Sonderforschungsbereich 504 Publications 05-27, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
  17. 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.
  18. Monderer, Dov & Shapley, Lloyd S., 1996. "Potential Games," Games and Economic Behavior, Elsevier, vol. 14(1), pages 124-143, May.
  19. Steffen Huck & Hans-Theo Normann & Joerg Oechssler, 1997. "Learning in Cournot Oligopoly - An Experiment," Game Theory and Information 9707009, EconWPA, revised 22 Jul 1997.
  20. Rajiv Sarin & Farshid Vahid, 2004. "Strategy Similarity and Coordination," Economic Journal, Royal Economic Society, vol. 114(497), pages 506-527, 07.
  21. Steffen Huck & Hans-Theo Normann & Joerg Oechssler, 2004. "Through Trial and Error to Collusion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 205-224, 02.
  22. Schipper, Burkhard C, 2011. "Strategic control of myopic best reply in repeated games," MPRA Paper 30219, University Library of Munich, Germany.
  23. McCabe, Kevin & Houser, Daniel & Ryan, Lee & Smith, Vernon & Trouard, Ted, 2001. "A Functional Imaging Study of Cooperation in Two-Person reciprocal Exchange," MPRA Paper 5172, University Library of Munich, Germany.
  24. Walker, James M. & Smith, Vernon L. & Cox, James C., 1987. "Bidding behavior in first price sealed bid auctions : Use of computerized Nash competitors," Economics Letters, Elsevier, vol. 23(3), pages 239-244.
  25. Roth, Alvin E & Schoumaker, Francoise, 1983. "Expectations and Reputations in Bargaining: An Experimental Study," American Economic Review, American Economic Association, vol. 73(3), pages 362-72, June.
  26. Kirchkamp, Oliver & Nagel, Rosemarie, 2007. "Naive learning and cooperation in network experiments," Games and Economic Behavior, Elsevier, vol. 58(2), pages 269-292, February.
  27. Daniel Houser & Robert Kurzban, 2002. "Revisiting Kindness and Confusion in Public Goods Experiments," American Economic Review, American Economic Association, vol. 92(4), pages 1062-1069, September.
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