whichimpliesthat: Pr(ˆq q 1 d(1/ n+ϵ)) e nϵ

To extend this and adapt other results to our setting, we could now apply the Simulation Lemma [1]to bound the value difference given the model error,or alternatively, develop the theory in the direction of[55]andrelated work. Code is available at https://github.com/spitis/mocoda Forexample, in2d Navigation,themaskfunction was implementedasfollows: def Mask2dNavigation(input_tensor): """ accepts B x num_sa_features, and returns B x num_parents x num_children """ # base local mask mask = torch.tensor( Theadvantageofthisapproach isthat we can easily do conditional sampling incase of overlapping parent sets. The CQL implementation uses SAC [17].