SARSA(0) Reinforcement Learning over Fully Homomorphic Encryption

Jihoon Suh, Takashi Tanaka
{"title":"SARSA(0) Reinforcement Learning over Fully Homomorphic Encryption","authors":"Jihoon Suh, Takashi Tanaka","doi":"10.23919/SICEISCS51787.2021.9495321","DOIUrl":null,"url":null,"abstract":"We consider a cloud-based control architecture in which the local plants outsource the control synthesis task to the cloud. In particular, we consider a cloud-based reinforcement learning (RL), where updating the value function is outsourced to the cloud. To achieve confidentiality, we implement computations over Fully Homomorphic Encryption (FHE). We use a CKKS encryption scheme and a modified SARSA(0) reinforcement learning to incorporate the encryption-induced delays. We then give a convergence result for the delayed updated rule of SARSA(0) with a blocking mechanism. We finally present a numerical demonstration via implementing on a classical pole-balancing problem.","PeriodicalId":395250,"journal":{"name":"2021 SICE International Symposium on Control Systems (SICE ISCS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 SICE International Symposium on Control Systems (SICE ISCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/SICEISCS51787.2021.9495321","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

We consider a cloud-based control architecture in which the local plants outsource the control synthesis task to the cloud. In particular, we consider a cloud-based reinforcement learning (RL), where updating the value function is outsourced to the cloud. To achieve confidentiality, we implement computations over Fully Homomorphic Encryption (FHE). We use a CKKS encryption scheme and a modified SARSA(0) reinforcement learning to incorporate the encryption-induced delays. We then give a convergence result for the delayed updated rule of SARSA(0) with a blocking mechanism. We finally present a numerical demonstration via implementing on a classical pole-balancing problem.
基于全同态加密的SARSA(0)强化学习
我们考虑了一种基于云的控制架构,其中本地工厂将控制综合任务外包给云。特别是,我们考虑基于云的强化学习(RL),其中更新价值函数外包给云。为了实现机密性,我们在完全同态加密(FHE)上实现了计算。我们使用CKKS加密方案和改进的SARSA(0)强化学习来合并加密引起的延迟。然后给出了具有阻塞机制的SARSA(0)延迟更新规则的收敛结果。最后,我们通过对一个经典的极平衡问题的实现给出了数值演示。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信