In many situations, e.g., in financial and economic decision making, the decision results either in a money gain (or loss) and/or in the gain of goods that can be exchanged for money or for other goods. In such situations, interval uncertainty means that we do not know the exact amount of money that we will get for each possible decision, we only know lower and upper bounds on this amount. In this case, a natural idea is to assign a fair price to different alternatives, and then to use these fair prices to select the best alternative. In the talk, we show how to assign a fair price under interval uncertainty. We also explain how to assign a fair price in the case of more general types of uncertainty such as p-boxes (bounds on cumulative distribution function), twin intervals (when we only know approximate bounds), fuzzy values (when we have imprecise expert estimates of the gains), etc.
In other situations, e.g., when buying a house to live in or selecting a movie to watch, the result of the decision is the decision maker's own satisfaction. In such situations, a more adequate approach is to use utilities - a quantitative way of describing user's preferences. In this talk, after a brief introduction describing what are utilities, how to evaluate them, and how to make decisions based on utilities, we explain how to make decisions in situations with user uncertainty - a realistic situation when a decision maker cannot always decide which alternative is better for him or her.