In this study, we investigate risk averse solutions to stochastic submodular utility functions. We formulate the problem as a discrete optimization problem of conditional value-at-risk, and prove hardness results for this problem.
Maehara, T. (2015). Risk averse submodular utility maximization. Operations Research Letters, 43(5), 526–529. https://doi.org/10.1016/j.orl.2015.08.001