Building agent-based hybrid intelligent systems: A case study

Zhang, Z; Zhang, C

Building agent-based hybrid intelligent systems: A case study

Zhang, Z Zhang, C

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Publication Type:: Journal Article
Citation:: Web Intelligence and Agent Systems, 2007, 5 (3), pp. 255 - 271
Issue Date:: 2007-10-23

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Field	Value	Language
dc.contributor.author	Zhang, Z	en_US
dc.contributor.author	Zhang, C https://orcid.org/0000-0001-5715-7154	en_US
dc.date.issued	2007-10-23	en_US
dc.identifier.citation	Web Intelligence and Agent Systems, 2007, 5 (3), pp. 255 - 271	en_US
dc.identifier.issn	1570-1263	en_US
dc.identifier.uri	http://hdl.handle.net/10453/4085
dc.description.abstract	Many complex problems (e.g., financial investment planning, foreign exchange trading, data mining from large/multiple databases) require hybrid intelligent systems that integrate many intelligent techniques (e.g., fuzzy logic, neural networks, and genetic algorithms). However, hybrid intelligent systems are difficult to develop because they have a large number of parts or components that have many interactions. On the other hand, agents offer a new and often more appropriate route to the development of complex systems, especially in open and dynamic environments. Thus, this paper discusses the development of an agent-based hybrid intelligent system for financial investment planning, in which a great number of heterogeneous computing techniques/packages are easily integrated into a unifying agent framework. This shows that agent technology can indeed facilitate the development of hybrid intelligent systems.	en_US
dc.relation.ispartof	Web Intelligence and Agent Systems	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Building agent-based hybrid intelligent systems: A case study	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	5	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
utslib.for	080105 Expert Systems	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0899 Other Information and Computing Sciences	en_US
utslib.for	1702 Cognitive Sciences	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/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.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	5	en_US

Abstract:

Many complex problems (e.g., financial investment planning, foreign exchange trading, data mining from large/multiple databases) require hybrid intelligent systems that integrate many intelligent techniques (e.g., fuzzy logic, neural networks, and genetic algorithms). However, hybrid intelligent systems are difficult to develop because they have a large number of parts or components that have many interactions. On the other hand, agents offer a new and often more appropriate route to the development of complex systems, especially in open and dynamic environments. Thus, this paper discusses the development of an agent-based hybrid intelligent system for financial investment planning, in which a great number of heterogeneous computing techniques/packages are easily integrated into a unifying agent framework. This shows that agent technology can indeed facilitate the development of hybrid intelligent systems.

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http://hdl.handle.net/10453/4085