A Computation Method In Robust Bayesian Decision Theory

摘要

We propose a method for computing the range of the optimal decisions when the utility function runs through a class h. The class h has constraints on the values and the shape of the utility functions. A discretization method enables to easily approximate the optimal decision associated with a particular utility function u∈ h. The range of optimal decisions is computed by a Monte Carlo optimization method. An example is provided with numerical results.