A general framework for explaining the results of a multi-attribute preference model

DOI10.1016/j.artint.2010.11.008zbMath1231.91084OpenAlexW2091144542MaRDI QIDQ646550

Christophe Labreuche

Publication date: 17 November 2011

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2010.11.008

zbMATH Keywords

decision theorypreferencesweightargumentation

Mathematics Subject Classification ID

Management decision making, including multiple objectives (90B50) Utility theory (91B16) Individual preferences (91B08)

Related Items (10)

Explaining robust additive utility models by sequences of preference swaps ⋮ Explanation with the Winter value: efficient computation for hierarchical Choquet integrals ⋮ An efficient SAT formulation for learning multiple criteria non-compensatory sorting rules from examples ⋮ A reward-based approach for preference modeling: a case study ⋮ Multiple criteria sorting models and methods. II: Theoretical results and general issues ⋮ Preferential reducts and constructs in robust multiple criteria ranking and sorting ⋮ A formal framework for deliberated judgment ⋮ Learning non-compensatory sorting models using efficient SAT/MaxSAT formulations ⋮ Explanation with the winter value: efficient computation for hierarchical Choquet integrals ⋮ The logical encoding of Sugeno integrals

Uses Software

• CP-nets
• M-MACBETH

Cites Work

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