On the Application and Interpretation of Learning Models

  • Ernan Haruvy
  • Ido Erev


Recent research in experimental economics suggests that simple models of learning can have nontrivial practical implications. For example, our research suggests that learning models can be used to design optimal pricing policy (Haruvy & Erev, 2000), efficient rule enforcement rules (Perry, Erev & Haruvy, 2000; Shany & Erev, 2000), efficient bonus systems (Haruvy, Erev, and Perry, 2000) and even optimal gambling devices (Haruvy, Erev, and Sonsino, 2000).


Learn Model Economic Behavior Normal Form Game Mean Square Distance Optimal Price Policy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Bereby-Meyer, Y., and I. Erev (1998). “On Learning To Become a Successful Loser: A Comparison of Alternative Abstractions of Learning Processes in the Loss Domain.” Journal of Mathematical Psychology 42, 266–86.CrossRefGoogle Scholar
  2. Camerer, C., and T. Ho (1997). “EWA Learning in Games: Preliminary Estimates from Weak-Link Games.” In Games and Human Behavior: Essays in Honor of Amnon Rapoport, edited by David V. Budescu, I. Erev, and Rami Zwick. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  3. Camerer, C., and T. Ho (1998). “EWA Learning in Coordination Games: Probability Rules, Heterogeneity, and Time-Variation.” Journal of Mathematical Psychology 42, 305–26.CrossRefGoogle Scholar
  4. Camerer, C., and T. Ho (1999a). “Experience-Weighted Attraction Learning in Games: Estimates from Weak-Link Games.” Chap. 3 in Games and Human Behavior, edited by David V. Budescu, Ido Erev, and Rami Zwick, 31–52. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  5. Camerer, C., and T. Ho (1999b). “Experience-Weighted Attraction Learning in Normal Form Games.” Econometrica 67, 827–74.CrossRefGoogle Scholar
  6. Camerer, C., T. Ho, and X. Wang (2000). “Individual Differences in the EWA Learning with Partial Payoff Information.” Working Paper.Google Scholar
  7. Cheung, Y-W, and D. Friedman (1994). “Learning in Evolutionary Games: Some Laboratory Results.” Working Paper No. 303, Economics, UCSC.Google Scholar
  8. Cheung, Y.-W., and D. Friedman (1997). “Individual Learning in Normal Form Games: Some Laboratory Results.” Games and Economic Behavior 19, 46–76.CrossRefGoogle Scholar
  9. Cheung, Y.-W, and D. Friedman (1998). “Comparison of Learning and Replicator Dynamics Using Experimental Data.“ Journal of Economic Behavior and Organization 35, 263–80.CrossRefGoogle Scholar
  10. Daniel, T. E., D. A. Seale, and A. Rapoport (1998). ”Strategic Play and Adaptive Learning in Sealed Bid Bargaining Mechanism.“ Journal of Mathematical Psychology 42, 133–66.CrossRefGoogle Scholar
  11. Erev, I., and E. Haruvy (2000). ”On the Potential Uses and Current Limitations of Data Driven Learning Models.“ Technion Working Paper.Google Scholar
  12. Erev, I., and A. Roth (1998). “Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique Mixed Strategy Equilibria.” American Economic Review 88, 848–81.Google Scholar
  13. Erev, I., Y. Bereby-Meyer, and A. Roth (1999). “The Effect of Adding a Constant to All Payoffs: Experimental Investigation, and Implications for Reinforcement Learning Models.” Journal of Economic Behavior and Organization 39, 111–28.CrossRefGoogle Scholar
  14. Fudenberg, D., and D. K. Levine (1998). The Theory of Learning in Games. Cambridge: MIT Press.Google Scholar
  15. Haruvy, E., and I. Erev (2000). “When to Pursue Variable Pricing: The Relationship Between Price Format and Quality.” Mimeo.Google Scholar
  16. Haruvy, E., I. Erev, and O. Perry (2000). “Probabilistic Employee Incentives.” Mimeo. Haruvy, E., I. Erev, and D. Sonsino (2000). “The Medium Prizes Paradox: Evidence From a Simulated Casino” Mimeo.Google Scholar
  17. Haruvy, E., D. O. Stahl, and P. W. Wilson (forthcoming). “Modeling and Testing for Heterogeneity in Observed Strategic Behavior.” Review of Economics and Statistics.Google Scholar
  18. Kirman, A. P. (1992). “Whom or What Does the Representative Individual Represent?” Journal of Economic Perspectives 6, 117–36.CrossRefGoogle Scholar
  19. Lucas, R. E. Jr. (1976). “Econometric Policy Evaluation: A Critique.” Carnegie-Rochester Conference Series on Public Policy 1, 19–46.CrossRefGoogle Scholar
  20. Nerlove, M. (1958). “Distributed Lags and Demand Analysis.” USDA Handbook No. 141, Government Printing Office.Google Scholar
  21. Roth, A., and I. Erev (1995). “Learning in Extensive Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Term.” Games and Economic Behavior 8, 164–212.CrossRefGoogle Scholar
  22. Roth, A. E., I. Erev, R. L. Slonim, and G. Barron (2000). “Learning and Equilibrium as Useful Approximations: Accuracy of Prediction on Randomly Selected Constant Sum Games.” Working Paper, Harvard University.Google Scholar
  23. Sarin, R., and F. Vahid (1999). “Payoff Assessments without Probabilities: A Simple Dynamic Model of Choice.” Games and Economic Behavior 28, 294–309.CrossRefGoogle Scholar
  24. Stahl, D. O. (1996). “Boundedly Rational Rule Learning in a Guessing Game.” Games and Economic Behavior 16, 303–30.CrossRefGoogle Scholar
  25. Stahl, D. O. (2000). “Action Reinforcement Learning versus Rule Learning.” Working Paper, University of Texas.Google Scholar
  26. Stahl, D. O. (2001). “Population Rule Learning in Symmetric Normal-Form Games: Theory and Evidence.” Journal of Economic Behavior and Organization 45, 19–35.CrossRefGoogle Scholar
  27. Stahl, D. 0., and P. W. Wilson (1994). “Experimental Evidence on Players’ Models of Other Players:’ Journal of Economic Behavior and Organization 25, 309–27.CrossRefGoogle Scholar
  28. Stahl, D. O., and P. W. Wilson (1995). “On Players’ Models of Other Players-Theory and Experimental Evidence.” Games and Economic Behavior 10, 213–54.CrossRefGoogle Scholar
  29. Stoker, T. M. (1993). “Empirical Approaches to the Problem of Aggregation over Individuals” Journal of Economic Literature 31, 1827–74.Google Scholar

Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Ernan Haruvy
    • 1
  • Ido Erev
    • 2
  1. 1.University of Texas at DallasUSA
  2. 2.Technion — Israel Institute of TechnologyIsrael

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