Reasoning With Conditional Ceteris Paribus Preference Statements
in Proc. Fifteenth
Conference on Uncertainty in Artificial
Intelligence (UAI-99).
Abstract
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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