Learning Preferences in Lexicographic Choice Logic

Karima Sedki, Karima Sedki, Nada Boudegzdame, Nada Boudegzdame, Jean Lamy, Jean Lamy, Rosy Tsopra, Rosy Tsopra

2023

Abstract

Lexicographic Choice Logic (LCL) is a variant of Qualitative Choice Logic which is a logic-based formalism for preference handling. The LCL logic extends the propositional logic with a new connective (⃗⋄ ) to express preferences. Given a preference x⃗⋄ y, satisfying both x and y is the best option, the second best option is to satisfy only x, and satisfying only y is the third best option. Satisfying neither x nor y is not acceptable. In this paper, we propose a method for learning preferences in the context of LCL. The method is based on an adaptation of association rules based on the APRIORI algorithm. The adaptation consists essentially of using variations of the support and confidence measures that are suitable for LCL semantic.

Paper Citation

in Harvard Style

Sedki K., Boudegzdame N., Lamy J. and Tsopra R. (2023). Learning Preferences in Lexicographic Choice Logic. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 1012-1019. DOI: 10.5220/0011891300003393

in Bibtex Style

@conference{icaart23,
author={Karima Sedki and Nada Boudegzdame and Jean Lamy and Rosy Tsopra},
title={Learning Preferences in Lexicographic Choice Logic},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={1012-1019},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011891300003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Learning Preferences in Lexicographic Choice Logic
SN - 978-989-758-623-1
AU - Sedki K.
AU - Boudegzdame N.
AU - Lamy J.
AU - Tsopra R.
PY - 2023
SP - 1012
EP - 1019
DO - 10.5220/0011891300003393