Craig Boutilier
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: cebly@cs.toronto.edu
Relu Patrascu
Dept. of Computer Science
University of Waterloo
Waterloo, ON, N2L 3G1
email: rpatrasc@cs.uwaterloo.ca
Pascal Poupart
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: ppoupart@cs.toronto.edu
Dale Schuurmans
Dept. of Computer Science
University of Waterloo
Waterloo, ON, N2L 3G1
email: dale@cs.uwaterloo.ca
Abstract
In many situations, a set of hard constraints encodes
the feasible configurations of some system or product
over which users have preferences. We
consider the problem of computing a best feasible solution when the
user's utilities are partially known. Assuming bounds on utilities,
efficient mixed integer linear programs are devised to compute the
solution with minimax regret while exploiting generalized additive
structure in a user's utility function.
To appear, CP2003
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