A method for processing sequentially acquired information is developed in which a decision makers uncertainty concerning the utility of this information is modeled by interval-valued random functions. Interval-valued estimates of the expected utility of each specific course of action chosen from a finite set of possible courses of action are developed. It is assumed that the uncertainty concerning the utility of the various courses of action tends to decrease as information increases, and certain reasonable conditions on the process of updating the estimated utilities are imposed. Under the conditions cited above it is shown that for each possible course of action, the sequential interval estimates of the expected utility forms a set-valued supermartingale with respect to a sequence of expanding σ-fields generated by the history of the information acquisition process