有限预算共识与最大共识水平的群体决策

IF 6.6 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Huanhuan Zhang , Dongjie Guo , Yifeng Ma
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引用次数: 0

摘要

群体决策通常需要进行深入的讨论,形成整个群体都能接受的共识,近年来吸引了越来越多的研究。尽管对软共识进行了广泛的研究,但共识水平与共识成本之间的关系尚不清楚。这项研究首次建立了一个精确的数学关系,表明更高的共识水平需要更大的共识成本。这一发现为共识建模提供了重要的理论基础。认识到达成共识的成本不可能是无限的,必须在一定的预算范围内,我们开发了一个模型来确定在有限预算下可实现的最大共识水平。探讨并建立了非合作者的共识模型。提出的模型应用于在线借贷平台,提供了一个实用的框架来衡量共识水平,并在有限的预算内实现贷方和借款人之间的软共识。这项工作有助于理解共识水平和共识成本之间的关系,以及在有限预算下实现最大可能的共识水平,这与资源有限的情况有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Limited-budget consensus with maximum consensus level for group decision making
Group decision making usually requires in-depth discussions to form a consensus acceptable to the entire group, which has attracted more and more research in recent years. Despite extensive studies on soft consensus, the relationship between consensus level and consensus cost remains unclear. This study establishes—for the first time—a precise mathematical relationship demonstrating that higher consensus levels require proportionally greater consensus costs. This finding provides critical theoretical grounding for consensus modeling. Recognizing that the cost of achieving consensus cannot be infinite and must be within a certain budget, we develop a model to determine the maximum achievable consensus level under a limited-budget. The consensus model with non-cooperators is also explored and formulated. The proposed models are applied to online lending platforms, providing a practical framework for measuring consensus levels and achieving soft consensus between lenders and borrowers within a limited-budget. This work contributes to understanding the relationship between consensus level and consensus cost, as well as the achievement of the maximum possible consensus level under limited-budget, which is relevant in scenarios where resources are finite.
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来源期刊
Applied Soft Computing
Applied Soft Computing 工程技术-计算机:跨学科应用
CiteScore
15.80
自引率
6.90%
发文量
874
审稿时长
10.9 months
期刊介绍: Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities. Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.
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