Preference Modeling by Weighted Goals with Max Aggregation
Joel Uckelman, Ulle Endriss

Abstract:
Logic-based preference representation languages are promising
for expressing preferences over combinatorial domains.
Sets of weighted formulas, called goalbases, can be used to
define several such languages. How goalbases are translated
into utility functions---that is, by what aggregation function
this is done---is a crucial component of this type of language.
In this paper, we consider the properties of several goalbase
languages which use max as their aggregation function.
In particular, we examine the expressivity, succinctness and
complexity of such languages.