Expedient and Monotone Learning Rules
AbstractThis paper considers learning rules for environments in which little prior and feedback information is available to the decision maker. Two properties of such learning rules are studied: absolute expediency and monotonicity. Both require that some aspect of the decision maker's performance improves from the current period to the next. The paper provides some necessary, and some sufficient conditions for these properties. It turns out that there is a large variety of learning rules that have the properties. However, all learning rules that have these properties are related to the replicator dynamics of evolutionary game theory. For the case in which there are only two actions, it is shown that one of the absolutely expedient learning rules dominates all others. Copyright The Econometric Society 2004.
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Bibliographic InfoArticle provided by Econometric Society in its journal Econometrica.
Volume (Year): 72 (2004)
Issue (Month): 2 (03)
Other versions of this item:
- Tilman Borgers & Antonio Morales & Rajiv Sarin, 2010. "Expedient and Monotone Learning Rules," Levine's Working Paper Archive 625018000000000099, David K. Levine.
- Tilman Börgers & Rajiv Sarin & Antonio J. Morales, 2001. "Expedient and Monotone Learning Rules," Economic Working Papers at Centro de Estudios Andaluces E2001/06, Centro de Estudios Andaluces.
- 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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