Evolutionary agents for intelligent transport systems

Jong Yih Kuo, Shin-Jie Lee, Chia Ling Wu, Nien Lin Hsueh, Jonathan Lee

研究成果: Article

6 引文 斯高帕斯(Scopus)

摘要

When agents are initially created, they have little knowledge and experience with relatively low capability. They strive to adapt themselves to the changing environment. It is an advantage if they have the ability to learn and evolve. This paper addresses evolution of intelligent agents in transport information system. Fuzzy theory and ontological reasoning approach are proposed as evolution mechanisms, and fuzzy soft goal is introduced to facilitate the evolution process. Genetic programming operators are employed to restructure agents in the proposed multi-agent evolution cycle. We have also built an agent system to demonstrate our approach.

原文English
頁(從 - 到)85-93
頁數9
期刊International Journal of Fuzzy Systems
7
發行號2
出版狀態Published - 2005 六月 1

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

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  • 引用此

    Kuo, J. Y., Lee, S-J., Wu, C. L., Hsueh, N. L., & Lee, J. (2005). Evolutionary agents for intelligent transport systems. International Journal of Fuzzy Systems, 7(2), 85-93.