An Efficient Algorithm to Compute Distance Between Lexicographic Preference Trees
Abstract
Very often, we have to look into multiple agents' preferences, and compare or aggregate them. In this paper, we consider the well-known model, namely, lexicographic preference trees (LP-trees), for representing agents' preferences in combinatorial domains. We tackle the problem of calculating the dissimilarity/distance between agents' LP-trees. We propose an algorithm LpDis to compute the number of disagreed pairwise preferences between agents by traversing their LP-trees. The proposed algorithm is computationally efficient and allows agents to have different attribute importance structures and preference dependencies.
Cite
Text
Li and Kazimipour. "An Efficient Algorithm to Compute Distance Between Lexicographic Preference Trees." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/262Markdown
[Li and Kazimipour. "An Efficient Algorithm to Compute Distance Between Lexicographic Preference Trees." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/li2018ijcai-efficient/) doi:10.24963/IJCAI.2018/262BibTeX
@inproceedings{li2018ijcai-efficient,
title = {{An Efficient Algorithm to Compute Distance Between Lexicographic Preference Trees}},
author = {Li, Minyi and Kazimipour, Borhan},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2018},
pages = {1898-1904},
doi = {10.24963/IJCAI.2018/262},
url = {https://mlanthology.org/ijcai/2018/li2018ijcai-efficient/}
}