• DocumentCode
    2409786
  • Title

    Case-based introspective learning

  • Author

    Shi, Zhongzhi ; Zhang, Sulan

  • Author_Institution
    Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing, China
  • fYear
    2005
  • fDate
    8-10 Aug. 2005
  • Firstpage
    43
  • Lastpage
    48
  • Abstract
    Introspective learning, as a method to improve the learning efficiency, has become an active area of research. In this paper, introspective learning and a general introspective learning mode are discussed. Some related problems such as meta-level reasoning, taxonomy of failure, and the relation between case-based reasoning and introspective learning are represented. Based on the importance of case-based reasoning in introspective learning, a case representation and case retrieval mechanism appropriate to introspective learning are described in detail.
  • Keywords
    case-based reasoning; learning (artificial intelligence); case representation; case retrieval; case-based introspective learning; case-based reasoning; failure taxonomy; metalevel reasoning; Computers; Failure analysis; Intelligent systems; Learning systems; Machine learning; Performance analysis; Problem-solving; Psychology; Taxonomy; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Informatics, 2005. (ICCI 2005). Fourth IEEE Conference on
  • Print_ISBN
    0-7803-9136-5
  • Type

    conf

  • DOI
    10.1109/COGINF.2005.1532614
  • Filename
    1532614