• DocumentCode
    3591949
  • Title

    A Multi-heuristic Cooperative Ant Colony System for Optimizing Elimination Ordering of Bayesian Networks

  • Author

    Dong, Xuchu ; Ouyang, Dantong ; Ye, Yuxin ; Yu, Haihong ; Zhang, Yonggang

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Jilin Univ., Jilin, China
  • Volume
    2
  • fYear
    2010
  • Firstpage
    75
  • Lastpage
    78
  • Abstract
    To solve the problem of searching for an optimal elimination ordering of Bayesian networks, a novel effective heuristic, MinSum Weight, and an ACS approach incorporated with multi-heuristic mechanism are proposed. The ACS approach named MHC-ACS utilizes a set of heuristics to direct the ants moving in the search space. The cooperation of multiple heuristics helps ants explore more regions. Moreover, the most appropriate heuristic will be identified and be reinforced with the evolution of the whole system. Experiments demonstrate that MHC-ACS has a better performance than other swarm intelligence methods.
  • Keywords
    belief networks; optimisation; Bayesian networks; MinSum weight; multiheuristic cooperative ant colony system; multiheuristic mechanism; optimizing elimination ordering; swarm intelligence methods; Bayesian network; ant colony system; elimination ordering; heuristics; junction tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on
  • Print_ISBN
    978-1-4244-8482-9
  • Electronic_ISBN
    978-0-7695-4191-4
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2010.33
  • Filename
    5616398