Preference-based Constrained Optimization with CP-nets (2001)
| Venue: | Computational Intelligence |
| Citations: | 42 - 9 self |
BibTeX
@ARTICLE{Boutilier01preference-basedconstrained,
author = {Craig Boutilier and Ronen I. Brafman and Holger H. Hoos and David Poole},
title = {Preference-based Constrained Optimization with CP-nets},
journal = {Computational Intelligence},
year = {2001},
volume = {20},
pages = {137--157}
}
Years of Citing Articles
Bookmark
 |
 |
 |
 |
 |
 |
OpenURL
Abstract
Many AI tasks, such as product configuration, decision support, and the construction of autonomous agents, involve a process of constrained optimization, that is, optimization of behavior or choices subject to given constraints. In this paper we present an approach for constrained optimization based on a set of hard constraints and a preference ordering represented using a CP-network - a graphical model for representing qualitative preference information. This approach offers both pragmatic and computational advantages. First, it provides a convenient and intuitive tool for specifying the problem, and in particular, the decision maker's preferences. Second, it provides an algorithm for finding the most preferred feasible outcomes that has the following anytime property: the set of preferred feasible outcomes are enumerated without backtracking. In particular, the first feasible solution generated by this algorithm is optimal.
