Facilitating the use of multi-attribute utility theory in expert systems: an aid for identifying the right relative importance weights of attributes

摘要

In general, expert system applications to real cases involve making decisions, i.e. selecting a suitable action among a set of possible alternative actions. A well-known sandard method for modelling decision problems is the so-called multi-attribute utility theory (MAU), a method in which the alternatives are viewed in terms of their attributes. A set of attributes are identified and a specific value and a suitable relative importance weight are assigned to each attribute.