Finite horizon sequential decision problems with a temporal von NeumannMorgenstern criterion are analyzed. This criterion, as developed in [7], is a generalization of von Neumann-Morgenstern (expected) utility of the vector of rewards, wherein an individual's preferences concerning the timing of the resolution of uncertainty are taken into account. The preference theory underlying this criterion is reviewed and then extended in natural fashion to yield preferences for strategies in sequential decision problems. The main result is that value functions for sequential decision problems can be defined by a dynamic programming recursion using the functions which represent the original preferences, and these value functions represent the preferences defined on strategies. This permits citation of standard results from the dynamic programming literature, concerning the existence of (memoryless) strategies which are optimal with respect to the given preference relation.

We consider dynamic choice behavior under conditions of uncertainty, with emphasis on the timing of the resolution of uncertainty.Choice behavior in which an individual distinguishes between lotteries based on the times at which their uncertainty resolves is axiomatized and represented, thus the result is choice behavior which cannot be represented by a single cardinal utility function on the vector of payoffs.Both descriptive and normative treatments of the problem are given and are shown to be equivalent.Various specializations are provided, including an extension of "separable" utility and representation by a single cardinal utility function.