An Axiomatization of Learning Rules when Counterfactuals are not Observed
In this paper we study learning procedures when counterfactuals (payoffs of not chosen actions) are not observed. The decision maker reasons in two steps: First, she updates her propensities for choosing each action after every payoff experience, where propensities can be interpreted as preferences. Then, she transforms these propensities into choice probabilities. We introduce a set of axioms on how propensities are updated and on how these propensities are translated into choices and study the decision marker's behavior when such axioms are in place. Our characterization includes the linear reinforcement learning rule from Roth and Erev (1995).
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Volume (Year): 12 (2012)
Issue (Month): 1 (July)
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References listed on IDEAS
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- Tilman Börgers & Antonio J. Morales & Rajiv Sarin, 2004.
"Expedient and Monotone Learning Rules,"
Econometric Society, vol. 72(2), pages 383-405, 03.
- 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.
- Tilman Borgers & Antonio Morales & Rajiv Sarin, 2010. "Expedient and Monotone Learning Rules," Levine's Working Paper Archive 625018000000000099, David K. Levine.
- Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July. Full references (including those not matched with items on IDEAS)
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