ABSTRACT
Dynamic programming is an optimization technique which has the following components: a state space, a set of constraints, a strategy set, an optimization criterion, and state dynamics (Mangel and Clark, 1988). An important feature of this technique is that it takes into account the influence of an organism's current state and the current time on its behavior (Houston and McNamara, 1988). The current behavior governs the organism's future state and, consequently, its behavior. This interdependence of state and behavior, mediated by time, allows for the calculation of a feedback control policy, which is a strategy for optimizing some performance criterion.
