A characterization of the existence of succinct linear representation of subset-valuations

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.2023.102779
Saša Pekeč
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Abstract

Decisions that involve bundling or unbundling a large number of objects, such as deciding on the bundle structure or optimizing bundle prices, are based on underlying valuation function over the set of all possible bundles. Given that the number of possible bundles (i.e., subsets of the given set of objects) is exponential in the number of objects, it is important for the decision-maker to be able to represent this valuation function succinctly. Identifying all structural sources of synergy in subset valuations might point to simple and concise representation of the valuation function. We characterize additive and multiplicative representations of synergies in subset valuations and subset utility, which in turn points to necessary and sufficient conditions for a succinct representation of subset valuations to exist.

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子集赋值的简洁线性表示的存在性的一个刻画
涉及捆绑或解除捆绑大量对象的决策,例如决定捆绑结构或优化捆绑价格,都是基于对所有可能捆绑集合的潜在估值函数。假设可能的束(即给定对象集合的子集)的数量是对象数量的指数,对于决策者来说,能够简洁地表示这个评估函数是很重要的。确定子集估值中协同作用的所有结构来源可能指向估值函数的简单而简洁的表示。我们描述了子集估值和子集效用中协同作用的加法和乘法表示,这反过来又指出了子集估值的简洁表示存在的充分必要条件。
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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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