Before revision:  The novelty is that it works in cases where robustness is described by a general family of probability measures that do not have to be dominated or time-consistent .
After revision:  The novelty is that it works under nondominated model uncertainty without any assumptions of time-consistency. As applications, we discuss robust utility maximization problems with moment constraints, Wasserstein constraints and Wasserstein penalties .