Reasoning With Conditional Ceteris Paribus Preference Statements

Craig Boutilier, Ronen I. Brafman, Holger H. Hoos, and David Poole

in Proc. Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI-99).


In many domains it is desirable to assess the preferences of users in a qualitative rather than quantitative way. Such representations of qualitative preference orderings form an important component of automated decision tools. We propose a graphical representation of preferences that reflects conditional dependence and independence of preference statements under a ceteris paribus (all else being equal) interpretation. Such a representation is often compact and arguably natural. We describe several search algorithms for dominance testing based on this representation; these algorithms are quite effective, especially in specific network topologies, such as chain- and tree-structured networks, as well as polytrees.

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