Choquet积分
偏爱
偏好学习
计算机科学
序数回归
人工智能
决策者
机器学习
有限理性
产品(数学)
数学
运筹学
统计
模糊逻辑
几何学
作者
Zhiqiang Liao,Huchang Liao,Xinli Zhang
标识
DOI:10.1016/j.eswa.2022.118977
摘要
Preference learning has been widely employed to predict decision-makers' preferences from historical information. This study develops a preference learning model for multiple criteria decision analysis where the decision-maker is supposed to be bounded rational and criteria are not completely independent of each other. The contextual Choquet integral is used as the aggregation function to address criteria interactions. The robust-ordinal-regression (ROR) technique is then applied to learn the preferences of decision-makers from the given preference data and provide robust decision recommendations. The proposed approach is illustrated by a numerical study concerning sustainable product evaluation.
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