More Efficient Off-Policy Evaluation through Regularized Targeted Learning

Aurélien F. Bibaut, Ivana Malenica, Nikos Vlassis +1

We study the problem of off-policy evaluation (OPE) in Reinforcement Learning (RL), where the aim is to estimate the performance of a new policy given historical data that may have…