Optimal Policies for Quantum Markov Decision Processes

doi:10.1007/s11633-021-1278-z

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	Optimal Policies for Quantum Markov Decision Processes
	Ming-Sheng Ying 1,2,3; Yuan Feng1 ; Sheng-Gang Ying 2
发表期刊	International Journal of Automation and Computing
ISSN	1476-8186
	2021
卷号	18 期号:3 页码:410-421
摘要	Markov decision process (MDP) offers a general framework for modelling sequential decision making where outcomes are random. In particular, it serves as a mathematical framework for reinforcement learning. This paper introduces an extension of MDP, namely quantum MDP (qMDP), that can serve as a mathematical model of decision making about quantum systems. We develop dynamic programming algorithms for policy evaluation and finding optimal policies for qMDPs in the case of finite-horizon. The results obtained in this paper provide some useful mathematical tools for reinforcement learning techniques applied to the quantum world.
关键词	Quantum Markov decision processes quantum machine learning reinforcement learning dynamic programming decision making
DOI	10.1007/s11633-021-1278-z
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44290
专题	学术期刊_Machine Intelligence Research
作者单位	1.Centre for Quantum Software and Information, University of Technology Sydney, NSW 2007, Australia 2.State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China 3.Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
推荐引用方式 GB/T 7714	Ming-Sheng Ying,Yuan Feng,Sheng-Gang Ying. Optimal Policies for Quantum Markov Decision Processes[J]. International Journal of Automation and Computing,2021,18(3):410-421.
APA	Ming-Sheng Ying,Yuan Feng,&Sheng-Gang Ying.(2021).Optimal Policies for Quantum Markov Decision Processes.International Journal of Automation and Computing,18(3),410-421.
MLA	Ming-Sheng Ying,et al."Optimal Policies for Quantum Markov Decision Processes".International Journal of Automation and Computing 18.3(2021):410-421.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
IJAC-2020-07-182.pdf（1163KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载