Reasoning About Soft Constraints and Conditional Preferences: Complexity Results and Approximation Techniques
Abstract
Many real life optimization problems contain both hard and soft constraints, as well as qualitative conditional preferences. However, there is no single formalism to specify all three kinds of information. We therefore propose a framework, based on both CP-nets and soft constraints, that handles both hard and soft constraints as well as conditional preferences efficiently and uniformly. We study the complexity of testing the consistency of preference statements, and show how soft constraints can faithfully approximate the semantics of conditional preference statements whilst improving the computational complexity.
Cite
Text
Domshlak et al. "Reasoning About Soft Constraints and Conditional Preferences: Complexity Results and Approximation Techniques." International Joint Conference on Artificial Intelligence, 2003.Markdown
[Domshlak et al. "Reasoning About Soft Constraints and Conditional Preferences: Complexity Results and Approximation Techniques." International Joint Conference on Artificial Intelligence, 2003.](https://mlanthology.org/ijcai/2003/domshlak2003ijcai-reasoning/)BibTeX
@inproceedings{domshlak2003ijcai-reasoning,
title = {{Reasoning About Soft Constraints and Conditional Preferences: Complexity Results and Approximation Techniques}},
author = {Domshlak, Carmel and Rossi, Francesca and Venable, K. Brent and Walsh, Toby},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2003},
pages = {215-220},
url = {https://mlanthology.org/ijcai/2003/domshlak2003ijcai-reasoning/}
}