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Plans of Action

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  • Roee Teper

Abstract

We introduce a decision theoretic foundation for a class of learning models in which thedecision maker's beliefs over the present uncertainty is dictated by the outcomes of herpast actions. This type of learning underlies models of strategic experimentation. Weconstruct a framework in which an alternative is a recursive function contingent at anystage on the outcomes of previous actions, and provide axiomatizations for subjectivediscounted expected utility maximization, both for independent actions and correlatedactions. We point out that models of strategic experimentation have inherent limitedobservability, which in turn leads to partial identification of the subjective belief structure. We show that a class of processes we refer to as strongly exchangeable are the fullcharacterization of Bayesianism in such environments.

Suggested Citation

  • Roee Teper, 2016. "Plans of Action," Working Paper 5859, Department of Economics, University of Pittsburgh.
  • Handle: RePEc:pit:wpaper:5859
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    File URL: https://www.econ.pitt.edu/sites/default/files/working_papers/WP16-005_0.pdf
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    References listed on IDEAS

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    1. Piermont, Evan & Takeoka, Norio & Teper, Roee, 2016. "Learning the Krepsian state: Exploration through consumption," Games and Economic Behavior, Elsevier, vol. 100(C), pages 69-94.
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    8. Eddie Dekel & Barton L Lipman & Aldo Rustichini & Todd Sarver, 2007. "Representing Preferences with a Unique Subjective State Space: A Corrigendum -super-1," Econometrica, Econometric Society, vol. 75(2), pages 591-600, March.
    9. Cooke, Kevin, 2017. "Preference discovery and experimentation," Theoretical Economics, Econometric Society, vol. 12(3), September.
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    Cited by:

    1. Piermont, Evan & Takeoka, Norio & Teper, Roee, 2016. "Learning the Krepsian state: Exploration through consumption," Games and Economic Behavior, Elsevier, vol. 100(C), pages 69-94.

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