• DocumentCode
    757425
  • Title

    Case-based systems

  • Author

    Juell, Paul ; Paulson, Patrick

  • Author_Institution
    North Dakota State Univ., Fargo, ND, USA
  • Volume
    18
  • Issue
    4
  • fYear
    2003
  • Firstpage
    60
  • Lastpage
    67
  • Abstract
    Because reinforcement-trained case-based reasoning systems derive a similarity function through interaction with their environment, they can adapt to user needs. RETCBR techniques let researchers apply case-based reasoning in domains where case similarity is difficult to define.
  • Keywords
    case-based reasoning; learning (artificial intelligence); RETCBR; reinforcement-trained case-based reasoning systems; similarity function; Databases; Environmental economics; Feedback; Humans; Immune system; Indexing; Learning; Libraries; Probes; Testing;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2003.1217629
  • Filename
    1217629
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=757425