Achieving Fairness with Intelligent Co Agents

Author:

,Reddy Katha RohanORCID

Abstract

Fairness in resource allocation is a important problem that has many real life consequences. Althoughmany algorithms that try to achieve envy free allocation, proportionality or min max share were proposed that tries to encapsulate fairness this does not suffice because it was inherently assumed that agents are not intelligent and there is uniformity in treatment. This is vastly different from real life where there are many scenarios where agents would actively try to sabotage or reduce the allocation given to their adversaries. Therefore all agents must not be treated the same way. As seen in economics cartels are where certain players collaborate and try to maximize their interest by undermining competition. This could lead to dangerous consequences and unfair means as seen withreal life examples of apple or google undermining competition by monopoly as explained clearly in (Das, Dhamal, Ghalme, Jain, & Gujar, 2022 [1])

Publisher

Lattice Science Publication (LSP)

Reference32 articles.

1. 1. Das, S., Dhamal, S., Ghalme, G., Jain, S., & Gujar, S. (2022).

2. Individual fairness in feature-basedpricing for monopoly markets.

3. 2. Jiang, J., & Lu, Z. (2019). Learning fairness in multi-agent

4. systems.

5. 3. Michelson, J. (2022). Developing a philosophical framework for

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3