1. A method for learning a management policy, comprising: receiving a set of one or more exemplars, wherein at least two of the exemplars comprise a (state, action) pair for a system, and at least one of the exemplars comprises a reward responsive to performing an action in a state; obtaining a set of one or more pairwise distances between one or more pairs of the one or more exemplars; applying nonlinear dimensionality reduction to the one or more exemplars and to the pairwise distances in order to embed the one or more exemplars into a lower dimensional space; and applying a reward-based learning method to the embedded exemplars in order to derive the management policy.