Formalizes counterfactual individual harm in RL and introduces a two-stage policy learning method with finite-sample guarantees on sub-optimality gap and harm rate control.
What are the statistical limits of offline rl with linear function approximation?arXiv preprint arXiv:2010.11895,
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Counterfactually Safe Reinforcement Learning
Formalizes counterfactual individual harm in RL and introduces a two-stage policy learning method with finite-sample guarantees on sub-optimality gap and harm rate control.