Ceteris paribus preference statements concisely represent preferences over outcomes or goals in a way natural to human thinking. Many decision making methods require an efficient method for comparing the desirability of two arbitrary goals. We address this need by presenting an algorithm for converting a set of qualitative ceteris paribus preferences into a quantitative utility function. Our algorithm is complete for a finite universe of binary features. Constructing the utility function can, in the worst case, take time exponential in the number of features. Common forms of independence conditions reduce the computational burden. We present heuristics using utility independence and constraint based search to achieve efficient utility functions.

Existing representations for multiattribute ceteris paribus preference statements have provided useful treatments and clear semantics for qualitative comparisons, but have not provided similarly clear representations or semantics for comparisons involving quantitative tradeoffs. We use directional derivatives and other concepts from elementary differential geometry to interpret conditional multiattribute ceteris paribus preference comparisons that state bounds on quantitative tradeoff ratios. This semantics extends the familiar economic notion of marginal rate of substitution to multiple continuous or discrete attributes. The same geometric concepts also provide means for interpreting statements about the relative importance of different attributes.

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