Nonhomogeneous Place-dependent Markov Chains, Unsynchronised AIMD, and Optimisation

F. Wirth, S. Stüdli, Jia Yuan Yu, M. Corless, R. Shorten
{"title":"Nonhomogeneous Place-dependent Markov Chains, Unsynchronised AIMD, and Optimisation","authors":"F. Wirth, S. Stüdli, Jia Yuan Yu, M. Corless, R. Shorten","doi":"10.1145/3312741","DOIUrl":null,"url":null,"abstract":"A stochastic algorithm is presented for a class of optimisation problems that arise when a group of agents compete to share a single constrained resource in an optimal manner. The approach uses intermittent single-bit feedback, which indicates a constraint violation and does not require inter-agent communication. The algorithm is based on a positive matrix model of AIMD, which is extended to the nonhomogeneous Markovian case. The key feature is the assignment of back-off probabilities to the individual agents as a function of the past average access to the resource. This leads to a nonhomogeneous Markov chain in an extended state space, and we show almost sure convergence of the average access to the social optimum.","PeriodicalId":17199,"journal":{"name":"Journal of the ACM (JACM)","volume":"40 1","pages":"1 - 37"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the ACM (JACM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3312741","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

A stochastic algorithm is presented for a class of optimisation problems that arise when a group of agents compete to share a single constrained resource in an optimal manner. The approach uses intermittent single-bit feedback, which indicates a constraint violation and does not require inter-agent communication. The algorithm is based on a positive matrix model of AIMD, which is extended to the nonhomogeneous Markovian case. The key feature is the assignment of back-off probabilities to the individual agents as a function of the past average access to the resource. This leads to a nonhomogeneous Markov chain in an extended state space, and we show almost sure convergence of the average access to the social optimum.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
非齐次位置相关马尔可夫链,非同步目标和优化
针对一类优化问题,提出了一种随机算法,该算法是在一组智能体以最优方式竞争共享单个约束资源时出现的。该方法使用间歇的单比特反馈,它指示约束违反并且不需要代理间通信。该算法基于AIMD的正矩阵模型,并将其推广到非齐次马尔可夫情况下。关键特征是将退出概率分配给单个代理,作为过去对资源的平均访问的函数。这导致了扩展状态空间中的非齐次马尔可夫链,并证明了接近社会最优的平均路径几乎肯定收敛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Synchronization Strings: Codes for Insertions and Deletions Approaching the Singleton Bound The Reachability Problem for Two-Dimensional Vector Addition Systems with States Invited Articles Foreword On Nonconvex Optimization for Machine Learning Exploiting Spontaneous Transmissions for Broadcasting and Leader Election in Radio Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1