• DocumentCode
    476182
  • Title

    Task matching & scheduling algorithm of hybrid avator team in collaborative virtual environments

  • Author

    Liu, Hui-yi ; Chen, Jing-fen

  • Author_Institution
    Comput. & Inf. Eng. Coll., Hohai Univ., Nanjing
  • Volume
    4
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    2384
  • Lastpage
    2389
  • Abstract
    With the coordination and collaboration mechanism in MAS (multi-agent system), a task matching & scheduling model of HA (hybrid avator) team in CVE (collaborative virtual environments ) is created. The energy consumption to complete the task is minimized by finding the best task matching & scheduling strategy on the precondition that HA agent in the team satisfies the dependence and restriction relation among all sub-tasks with common task. Exhaustive enumeration is traditionally used to achieve global optimization with huge system cost, which possibly leads to search combination explosion. In this paper, team task matching & scheduling algorithm based on genetic algorithm is introduced with simulation examples for its model of HA team. The experiment results show that the algorithm has a comparatively high efficiency in solving problem on team task matching & scheduling.
  • Keywords
    avatars; genetic algorithms; groupware; multi-agent systems; scheduling; collaborative virtual environments; energy consumption; genetic algorithm; global optimization; hybrid avatar team; multiagent system; task matching-scheduling algorithm; Cost function; Cybernetics; Educational institutions; Genetic algorithms; International collaboration; Iterative algorithms; Machine learning; Power engineering and energy; Scheduling algorithm; Virtual environment; Agent; CVE; Genetic algorithm; HA; Task matching & scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620804
  • Filename
    4620804