• DocumentCode
    2397093
  • Title

    Research on Scheduling in Multi-Softman System with the Learning Mode Based on Genetic Algorithms

  • Author

    Jie, Pang ; Shurong, Ning ; Guizhi, Li ; Yaoguang, Wei ; Xuyan, Tu

  • Author_Institution
    Sch. of Inf., Beijing Forestry Univ.
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1026
  • Lastpage
    1029
  • Abstract
    The concept, characteristics and models of Softman are discussed in this paper. An individual Softman overall model is given. Also the learning mode based on genetic algorithms which was used for the scheduling (decomposition of the task, distribution of sub-duties and multi-Softman parallel solution) in multi-Softman system is proposed. Genetic algorithms are mostly applied to the distribution of the task and in multi-Softman parallel solution
  • Keywords
    artificial life; genetic algorithms; learning (artificial intelligence); multi-agent systems; scheduling; genetic algorithms; learning mode; multiSoftman system; scheduling; Agricultural engineering; Artificial intelligence; Genetic algorithms; Humans; Intelligent agent; Intelligent networks; Intelligent robots; Learning; Samarium; Scheduling; AL; Softman; genetic algorithms; learning mode; scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on
  • Conference_Location
    Ft. Lauderdale, FL
  • Print_ISBN
    1-4244-0065-1
  • Type

    conf

  • DOI
    10.1109/ICNSC.2006.1673292
  • Filename
    1673292
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2397093