Bandit algorithms for policy learning: methods, implementation, and welfare-performance

Static supervised learning—in which experimental data serves as a training sample for the estimation of an optimal treatment assignment policy—is a commonly assumed framework of policy learning. An arguably more realistic but challenging scenario is a dynamic setting in which the planner performs ex...

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