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TitleTowards efficient selection of web services with reinforcement learning process
Creator
Date Issued2005
Conference Name17th International Conference on Tools with Artificial Intelligence
Source PublicationProceedings - 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)
ISBN0769524885
ISSN1082-3409
Volume2005
Pages372-376
Conference Date14-16 Nov. 2005
Conference PlaceHong Kong, China
Abstract

As an emerging technology for implementing web services over the Internet, mobile agent model has several advantages over the traditional RPC model. However, with the popularity of distributed networks (e.g. Internet), web service providers tend to rely on external resources to complete certain tasks. This definitely increases the difficulty in locating appropriate service providers according to clients' requirements in the new scenario. To address this issue, we propose a reinforcement learning process based on the mobile agent model, which makes agents more efficient and intelligent in selecting web service providers. Finally, an implementation of our prototype is presented. © 2005 IEEE.

DOI10.1109/ICTAI.2005.122
URLView source
Indexed ByCPCI-S
Language英语English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000234632500057
Scopus ID2-s2.0-33845889050
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/6988
CollectionResearch outside affiliated institution
Affiliation
1.Department of Computer Science,University of Hong Kong,Hong Kong,China
2.E-business,Technology Institute,University of Hong Kong,Hong Kong,China
3.Department of Computer Science,Nanjing University,Nanjing,China
Recommended Citation
GB/T 7714
Cai, Dongjun,Luo, Zongwei,Qian, Kunet al. Towards efficient selection of web services with reinforcement learning process[C], 2005: 372-376.
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