标题:Web Service Composition Based on Reinforcement Learning
作者:Yu, L[1];Zhou, JT[1];Wei, FQ[1];Gao, YQ[1];Yang, B[1]
作者全称:Yu Lei[1];Zhou Jiantao[1];Wei Fengqi[1];Gao Yongqiang[1];Yang Bo[1]
第一作者:Yu Lei
通讯作者:Yu, L
通讯作者地址:Yu, L (reprint author), Inner Mongolia Univ, Inner Mongolia Engn Lab Cloud Comp & Serv Softwar, Hohhot, Peoples R China.
年份:2015
语种:English
基金:IEEE Computer Society Technical Committee on Services Computing (TC-SVC);Services Computing Professional Interest Community (PIC) at IBM Research and Huawei;Services Society (SS)
文献类型:Proceedings Paper
WOS号:WOS:000380486400094
DOI号:10.1109/ICWS.2015.103
WOS类别:Engineering, Electrical & Electronic
研究方向:Engineering
关键词:Web service composition; optimal policy; partially observable markov; decision process; reinforcement learning algorithm
摘要:How we manage Web services depends on how we understand their variable parts and invariable parts. Studying them separately could make Web service res 更多
核心收录:SCOPUS;CPCI-S
资源类型:外文期刊论文
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