• DocumentCode
    950311
  • Title

    AI and Similarity

  • Author

    Rissland, Edwina L.

  • Author_Institution
    Massachusetts Univ., MA
  • Volume
    21
  • Issue
    3
  • fYear
    2006
  • Firstpage
    39
  • Lastpage
    49
  • Abstract
    As AI moves into the second half of its first century, we certainly have much to cheer about. For AI to become truly robust, we must further our understanding of similarity-driven reasoning, analogy, learning, and explanation. In this article, the author presents some suggested research directions
  • Keywords
    case-based reasoning; learning (artificial intelligence); AI learning; artificial intelligence; case-based reasoning; similarity-driven reasoning; Artificial intelligence; Character recognition; Cognition; Computational modeling; Humans; Knowledge representation; Machine learning; Problem-solving; Robustness; Solids; AI and law; case-based reasoning; concept change; concepts; examples; explanation; hypotheticals; open-texture; similarity;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2006.38
  • Filename
    1637349
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=950311