Inference on the Value of Policy Improvement in Adaptive Experiments
In this paper, we develop an asymptotically normal estimator for the value of policy improvement (VPI) under adaptively collected data. This value, which is defined as the gap between the value of the best treatment policy in a class and that of a baseline policy, gauges whether or not it is worth deploying a personali...
Justin Whitehouse, Emma Brunskill, Vasilis Syrgkanis
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