Constraint-based preferential optimization

Authors:
S. Prestwich;F. Rossi;K. B. Venable;T. Walsh
Affiliations:
University College Cork, Ireland;University of Padova, Italy;University of Padova, Italy;NICTA and UNSW, Australia
Venue:
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Year:
2005

Citing 5
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Comparing the notions of optimality in CP-nets, strategic games and soft constraints

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The computational complexity of dominance and consistency in CP-Nets

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Preference reasoning

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Abstract

We first show that the optimal and undominated outcomes of an unconstrained (and possibly cyclic) CP-net are the solutions of a set of hard constraints. We then propose a new algorithm for finding the optimal outcomes of a constrained CP-net which makes use of hard constraint solving. Unlike previous algorithms, this new algorithm works even with cyclic CP-nets. In addition. the algorithm is not tied to CP-nets, but can work with any preference formalism which produces a preorder over the outcomes. We also propose an approximation method which weakens the preference ordering induced by the CP-net, returning a larger set of outcomes, but provides a significant computational advantage. Finally, we describe a weighted constraint approach that allows to find good solutions even when optimals do not exist.