Optimal Learning by Experimentation
This paper considers a problem of optimal learning by experimentation by a single decisionmaker. Most of the analysis is concerned with the characterization of limit beliefs and actions. The authors take a two-stage approach to this problem: first, understand the case where the agent's payoff function is deterministic; then, address the additional issues arising when noise is present. Their analysis indicates that local properties of the payoff function (such as smoothness) are crucial in determining whether the agent eventually attains the true maximum payoff or not. The paper also makes a limited attempt at characterizing optimal experimentation strategies. Coauthors are Patrick Bolton, Christopher Harris, and Bruno Jullien. Copyright 1991 by The Review of Economic Studies Limited.
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Volume (Year): 58 (1991)
Issue (Month): 4 (July)
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