Most real-life decisions require the decision maker to make trade-offs in order to fulfill multiple conflicting objectives. This is especially true in medical decision making while selecting the optimal therapy plan from among competing therapy plans for a patient. Multi-attribute utility theory provides a framework to specify these trade-offs for optimal decision making based on the preferences of the decision maker. However traditional preference-assessment techniques are difficult to implement and rarely elicit the true preferences of the decision maker. We describe a new preference-assessment method based on the concept of knowledge maintenance where the preference model is changed each time it makes an incorrect recommendation. The method is implemented in a decision-theoretic system to evaluate competing three-dimensional radiation treatment plans. The preference-assessment method leads to preference models which perform better than preference models elicited using traditional assessment techniques.