• DocumentCode
    2610526
  • Title

    An improved critical diagnosis reasoning method

  • Author

    Xu, Yue ; Zhang, Chengqi

  • Author_Institution
    Dept. of Math. Stat. & Comput. Sci., New England Univ., Armidale, NSW, Australia
  • fYear
    1996
  • fDate
    16-19 Nov. 1996
  • Firstpage
    170
  • Lastpage
    173
  • Abstract
    Model-based diagnosis has the disadvantage of a high computational complexity. One way to overcome this disadvantage is to focus the diagnosis on a reduced diagnostic space. We propose an improved critical diagnosis reasoning method based on the method proposed by (Raiman et al., 1993). The method focuses the diagnosis on finding out the kernel diagnoses instead of the whole diagnoses. We give an updated definition of critical cover which we call "critical partition". The conditions satisfied by critical partition are relaxed compared with the conditions for critical cover. Correspondingly, a non-backtracking algorithm called Searching Critical Partition (SCP) to find out the critical partition is also proposed.
  • Keywords
    computational complexity; diagnostic expert systems; diagnostic reasoning; model-based reasoning; search problems; Searching Critical Partition; computational complexity; critical cover; critical diagnosis reasoning method; critical partition; kernel diagnoses; model-based diagnosis; nonbacktracking algorithm; reduced diagnostic space; Artificial intelligence; Computational complexity; Computer architecture; Distributed computing; Fault diagnosis; Kernel; Mathematical model; Mathematics; Partitioning algorithms; Statistical distributions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 1996., Proceedings Eighth IEEE International Conference on
  • ISSN
    1082-3409
  • Print_ISBN
    0-8186-7686-7
  • Type

    conf

  • DOI
    10.1109/TAI.1996.560448
  • Filename
    560448