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Strategic Experimentation


  • Patrick Bolton
  • Christopher Harris


This paper extends the classic two-armed bandit problem to a many-agent setting in which N players each face the same experimentation problem. The main change from the single-agent problem is that an agent can now learn from the current experimentation of other agents. Information is therefore a public good, and a free-rider problem in experimentation naturally arises. More interestingly, the prospect of future experimentation by others encourages agents to increase current experimentation, in order to bring forward the time at which the extra information generated by such experimentation becomes available. The paper provides an analysis of the set of stationary Markov equilibria in terms of the free-rider effect and the encouragement effect.

Suggested Citation

  • Patrick Bolton & Christopher Harris, 1999. "Strategic Experimentation," Econometrica, Econometric Society, vol. 67(2), pages 349-374, March.
  • Handle: RePEc:ecm:emetrp:v:67:y:1999:i:2:p:349-374

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    References listed on IDEAS

    1. Gul, Faruk & Postlewaite, Andrew, 1992. "Asymptotic Efficiency in Large Exchange Economies with Asymmetric Information," Econometrica, Econometric Society, vol. 60(6), pages 1273-1292, November.
    2. McAfee, R Preston & Reny, Philip J, 1992. "Correlated Information and Mechanism Design," Econometrica, Econometric Society, vol. 60(2), pages 395-421, March.
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