模态偏好结构

IF 2.2 4区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Mathematical Psychology Pub Date : 2023-08-01 DOI:10.1016/j.jmp.2023.102791
Davide Carpentiere , Alfio Giarlotta , Stephen Watson
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引用次数: 0

摘要

全预序是集合上的传递完备二元关系。一个n阶的模态偏好结构是一个由2 ^ n个二进制关系组成的字符串,在一个集合上,有一组总预购,通过取交集和并集给出所有关系。总预订量为0级结构,NaP-preferences (Giarlotta and Greco, 2013)为1级结构,GNaP-preferences (Carpentiere et al., 2022)为2级结构。利用传递相干性和混合完备性对任意阶的模态偏好结构进行了刻画。此外,我们展示了如何从其他低秩的结构中构造给定秩的结构。模态偏好结构出现在经济学和心理学中,在聚合主体群体的层次判断过程中,其中每个n个坐标代表决策过程的一个特征/阶段。
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Modal preference structures

A total preorder is a transitive and complete binary relation on a set. A modal preference structure of rank n is a string composed of 2 to the exponent n binary relations on a set such that there is a family of total preorders that gives all relations by taking intersections and unions. Total preorders are structures of rank zero, NaP-preferences (Giarlotta and Greco, 2013) are structures of rank one, and GNaP-preferences (Carpentiere et al., 2022) are structures of rank two. We characterize modal preference structures of any rank by properties of transitive coherence and mixed completeness. Moreover, we show how to construct structures of a given rank from others of lower rank. Modal preference structures arise in economics and psychology, in the process of aggregating hierarchical judgements of groups of agents, where each of the n coordinates represents a feature/stage of the decision procedure.

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来源期刊
Journal of Mathematical Psychology
Journal of Mathematical Psychology 医学-数学跨学科应用
CiteScore
3.70
自引率
11.10%
发文量
37
审稿时长
20.2 weeks
期刊介绍: The Journal of Mathematical Psychology includes articles, monographs and reviews, notes and commentaries, and book reviews in all areas of mathematical psychology. Empirical and theoretical contributions are equally welcome. Areas of special interest include, but are not limited to, fundamental measurement and psychological process models, such as those based upon neural network or information processing concepts. A partial listing of substantive areas covered include sensation and perception, psychophysics, learning and memory, problem solving, judgment and decision-making, and motivation. The Journal of Mathematical Psychology is affiliated with the Society for Mathematical Psychology. Research Areas include: • Models for sensation and perception, learning, memory and thinking • Fundamental measurement and scaling • Decision making • Neural modeling and networks • Psychophysics and signal detection • Neuropsychological theories • Psycholinguistics • Motivational dynamics • Animal behavior • Psychometric theory
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