On the optimal amount of experimentation in sequential decision problems
We provide a tight bound on the amount of experimentation under the optimal strategy in sequential decision problems. We show the applicability of the result by providing a bound on the cut-off in a one-arm bandit problem.
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Volume (Year): 80 (2010)
Issue (Month): 5-6 (March)
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References listed on IDEAS
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- Dinah Rosenberg & Eilon Solan & Nicolas Vieille, 2004.
"Social Learning in One-Arm Bandit Problems,"
1396, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Rosenberg, Dinah & Solan, Eilon & Vieille, Nicolas, 2009.
"Informational externalities and emergence of consensus,"
Games and Economic Behavior,
Elsevier, vol. 66(2), pages 979-994, July.
- Nicolas Vieille & Eilon Solan & Dinah Rosenberg, 2009. "Informational externalities and emergence of consensus," Post-Print hal-00464565, HAL.
- Godfrey Keller & Sven Rady & Martin Cripps, 2005.
"Strategic Experimentation with Exponential Bandits,"
Econometric Society, vol. 73(1), pages 39-68, 01.
- Cripps, Martin & Keller, Godfrey & Rady, Sven, 2003. "Strategic Experimentation with Exponential Bandits," Discussion Papers in Economics 4, University of Munich, Department of Economics.
- Cripps, Martin William & Keller, R Godfrey & Rady, Sven, 2003. "Strategic Experimentation with Exponential Bandits," CEPR Discussion Papers 3814, C.E.P.R. Discussion Papers.
- Patrick Bolton & Christopher Harris, 1999. "Strategic Experimentation," Econometrica, Econometric Society, vol. 67(2), pages 349-374, March.
- Dirk Bergemann & Juuso Valimaki, 1999.
"Experimentation in Markets,"
Cowles Foundation Discussion Papers
1214, Cowles Foundation for Research in Economics, Yale University.
- Monica Brezzi & Tze Leung Lai, 2000. "Incomplete Learning from Endogenous Data in Dynamic Allocation," Econometrica, Econometric Society, vol. 68(6), pages 1511-1516, November.
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