Derives optimal logging policies for minimizing off-policy evaluation error under known, unknown, and partially known target policies and reward distributions.
Proceedings of the 39th International Conference on Machine Learning (ICML) , pages =
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Logging Policy Design for Off-Policy Evaluation
Derives optimal logging policies for minimizing off-policy evaluation error under known, unknown, and partially known target policies and reward distributions.