Building agent-based hybrid intelligent systems: A case study

  • Authors:
  • Zili Zhang;Chengqi Zhang

  • Affiliations:
  • (Correspd. E-mail: zhangzl@swu.edu.cn) Faculty of Computer and Information Science, Southwest Univ., Chongqing 400715, China and School of Eng. and Info. Technol., Deakin University, Geelong Victo ...;Faculty of Information Technology, University of Technology, Sydney, PO Box 123 Broadway, NSW 2007 Australia

  • Venue:
  • Web Intelligence and Agent Systems
  • Year:
  • 2007

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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.