An agent-based framework for well-logging information management

Li, C; Zhang, C; Wang, M

An agent-based framework for well-logging information management

Li, C Zhang, C

Wang, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Conference on Active Media Technology, 2003, pp. 114 - 119
Issue Date:: 2003-10-17

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Field	Value	Language
dc.contributor.author	Li, C	en_US
dc.contributor.author	Zhang, C https://orcid.org/0000-0001-5715-7154	en_US
dc.contributor.author	Wang, M	en_US
dc.date.issued	2003-10-17	en_US
dc.identifier.citation	Proceedings of the International Conference on Active Media Technology, 2003, pp. 114 - 119	en_US
dc.identifier.isbn	9812383433	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1796
dc.description.abstract	In this paper, we contribute a framework based on multi-agent technique to manage large amounts of well-logging parameter graph information and store the data into Oracle database. We employed the idea of Gaia to design the framework, which consists of three levels, namely, role model level, agent type level and agent instance level. Four agent types, which correspond to the four roles, are proposed. We design the architectural model of agent instances with Open Agent Architecture. The experimental results show that all agents in the system can work cooperatively.	en_US
dc.relation.ispartof	Proceedings of the International Conference on Active Media Technology	en_US
dc.title	An agent-based framework for well-logging information management	en_US
dc.type	Conference Proceeding
utslib.for	080101 Adaptive Agents and Intelligent Robotics	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Chongqing, China	en_US
dc.location.activity	Sydney, AUSTRALIA
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/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

Abstract:

In this paper, we contribute a framework based on multi-agent technique to manage large amounts of well-logging parameter graph information and store the data into Oracle database. We employed the idea of Gaia to design the framework, which consists of three levels, namely, role model level, agent type level and agent instance level. Four agent types, which correspond to the four roles, are proposed. We design the architectural model of agent instances with Open Agent Architecture. The experimental results show that all agents in the system can work cooperatively.

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http://hdl.handle.net/10453/1796