Utility Functions for Ceteris Paribus Preferences

Abstract

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.

Efficient Distributed Skylining for Web Information Systems

“…Besides we will focus more closely on quality aspects of skyline queries. In this context especially a-posteriori quality assessments along the lines of our sampling technique and qualitative assessments like in [17] may help users to cope with large result sets. We will also investigate our proposed quality measures in more detail and evaluate their individual usefulness.…”

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“…al. have introduced ceterisparibus preferences between propositional formulas (Doyle, Shoham, & Wellman 1991;McGeachie & Doyle 2004). Boutilier and Brafman et.…”

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