1. A method for optimizing debt collection, comprising the steps of: using a computer to estimate a value function specifying an expected value of each of one or more collection actions for each of one or more states of a debtor; using a constrained reinforcement learning process to approximately estimate said value function with respect to a constrained Markov Decision Process formulation, to maximize long-term expected return throughout the course of a collection process, and to optimize collection resources within one or more organizations for maximum expected return subject to one or more given resource constraints for said organizations; and using a computer to provide an optimized debt collection policy as output in a machine-readable format.