Stationary multi-choice bandit problems
AbstractThis note shows that the optimal choice of k simultaneous experiments in a stationary multi-armed bandit problem can be characterized in terms of the Gittins index of each arm. The index characterization remains equally valid after the introduction of switching costs.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 25 (2001)
Issue (Month): 10 (October)
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Web page: http://www.elsevier.com/locate/jedc
Other versions of this item:
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
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- Hart E. Posen & Dirk Martignoni & Daniel A. Levinthal, 2013. "E Pluribus Unum: Organizational Size and the Efficacy of Learning," DRUID Working Papers 13-09, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
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- Keller, Godfrey & Oldale, Alison, 2003. "Branching bandits: a sequential search process with correlated pay-offs," Journal of Economic Theory, Elsevier, vol. 113(2), pages 302-315, December.
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