Agent services-driven plug-and-play in F-TRADE

Cao, L; Ni, J; Wang, J; Zhang, C

Agent services-driven plug-and-play in F-TRADE

Cao, L

Ni, J Wang, J Zhang, C

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 2004, 3339 pp. 917 - 922
Issue Date:: 2004-12-01

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Field	Value	Language
dc.contributor.author	Cao, L https://orcid.org/0000-0003-1562-9429	en_US
dc.contributor.author	Ni, J	en_US
dc.contributor.author	Wang, J	en_US
dc.contributor.author	Zhang, C https://orcid.org/0000-0001-5715-7154	en_US
dc.date.issued	2004-12-01	en_US
dc.identifier.citation	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 2004, 3339 pp. 917 - 922	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1944
dc.description.abstract	We have built an agent service-based enterprise infrastructure: F-TRADE. With its online connectivity to huge real stock data in global markets, it can be used for online evaluation of trading strategies and data mining algorithms. The main functions in the F-TRADE include soft plug-and-play, and back-testing, optimization, integration and evaluation of algorithms. In this paper, we'll focus on introducing the intelligent plug-and-play, which is a key system function in the F-TRADE. The basic idea for the soft plug-and-play is to build agent services which can support the online plug-in of agents, algorithms and data sources. Agent UML-based modeling, role model and agent services for the plug-and-play are discussed. With this design, algorithm providers, data source providers, and system module developers of the F-TRADE can expand system functions and resources by online plugging them into the F-TRADE. © Springer-Verlag Berlin Heidelberg 2004.	en_US
dc.relation.ispartof	Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Agent services-driven plug-and-play in F-TRADE	en_US
dc.type	Conference Proceeding
utslib.citation.volume	3339	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Cairns, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (International)
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - ACRI - Australia China Relations Institute
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	3339	en_US

Abstract:

We have built an agent service-based enterprise infrastructure: F-TRADE. With its online connectivity to huge real stock data in global markets, it can be used for online evaluation of trading strategies and data mining algorithms. The main functions in the F-TRADE include soft plug-and-play, and back-testing, optimization, integration and evaluation of algorithms. In this paper, we'll focus on introducing the intelligent plug-and-play, which is a key system function in the F-TRADE. The basic idea for the soft plug-and-play is to build agent services which can support the online plug-in of agents, algorithms and data sources. Agent UML-based modeling, role model and agent services for the plug-and-play are discussed. With this design, algorithm providers, data source providers, and system module developers of the F-TRADE can expand system functions and resources by online plugging them into the F-TRADE. © Springer-Verlag Berlin Heidelberg 2004.

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http://hdl.handle.net/10453/1944