Suppose at first that we are taking the approach of aggregating individual ratings. In this case, the goal of maximizing average satisfaction can be achieved by an aggregation function that computes some sort of average of the predicted satisfaction of each member for use as a basis for the selection of candidates (see Equation 20.2). The POCKET RESTAURANTFINDER (McCarthy [26]; cf. Section 20.2.1) applies a variant of this formula to the predicted ratings of restaurants by members of a group who are preparing to go out to dine together. The G.A.I.N. system of Pizzutilo et al. [32], which presents news items on a wall display or an information kiosk, uses a more complex variant of this formula that takes into account uncertainty about which users will be viewing the display at any given time; a similar procedure is applied in FIT (Goren-Bar and Glinansky [14]), which recommends TV shows for members of a family.