.png){kind=icon}
返回
Multi-dimensional fairness for auction-based resource allocation
.png){kind=icon}
OA
AI
DOI：10.1016/j.knosys.2014.09.009.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Multi-attribute resource allocation problems involve the allocation of resources on the basis of several attributes, therefore, the definition of a fairness method for this kind of auctions should be formulated from a multi-dimensional perspective. Under such point of view, fairness should take into account all the attributes involved in the allocation problem, since focusing on just a single attribute may compromise the allocations regarding the remainder attributes (e.g. incurring in delayed or bad quality tasks). In this paper, we present a multi-dimensional fairness approach based on priorities. For that purpose, a recurrent auction scenario is assumed, in which the auctioneer keeps track of winner and losers. From that information, the priority methods are defined based on the lost auctions number, the number of consecutive loses, and the fitness of their loser bids. Moreover, some methods contain a probabilistic parameter that enables handling wealth ranking disorders due to fairness. We test our approach in real-data based simulator which emulates an industrial production environment where several resource providers compete to perform different tasks. The results pointed that multi-dimensional fairness incentives agents to remain in the market whilst it improves the equity of the wealth distribution without compromising the quality of the allocation attributes. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Multi-attribute resource allocation
Multi-agent systems
Fairness
Auctions
Mechanism design
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
K
IF:
7.6
论文数:
1.2W
被引数:
4.5W
机构
引用论文
Schedule coordination through egalitarian recurrent multi-unit combinatorial auctions.png)
APPLIED INTELLIGENCE
APPLIED INTELLIGENCEIF3.5
PREAI
分享收藏分享收藏A spectrum of compromise aggregation operators for multi-attribute decision making用于多属性决策的折衷聚合算子谱OAAI
OAAI分享收藏Identification of Protein Subcellular Localization With Network and Functional Embeddings基于网络和功能嵌入的蛋白质亚细胞定位鉴定
OAAI
OAAI分享收藏
查看更多内容