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Conference Papers Year : 2023

Learning Preferences in Lexicographic Choice Logic

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.

Dates and versions

hal-04162803 , version 1 (16-07-2023)

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Karima Sedki, Nada Boudegzdame, Jean Lamy, Rosy Tsopra. Learning Preferences in Lexicographic Choice Logic. ICAART 2023 - 15th International Conference on Agents and Artificial Intelligence, Feb 2023, Lisbonne, Portugal. pp.1012-1019, ⟨10.5220/0011891300003393⟩. ⟨hal-04162803⟩
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