• DocumentCode
    2402388
  • Title

    Integration of qualitative and quantitative methods in visual reasoning

  • Author

    Narayanan, N. Hari ; Chandrasekaran, B.

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA
  • fYear
    1991
  • fDate
    1-2 Apr 1991
  • Firstpage
    272
  • Lastpage
    278
  • Abstract
    Describes how commonsense spatial reasoning is accomplished in a computational model that is primarily qualitative in nature, but which allows the smooth integration of quantitative methods as and when necessary. This model, termed visual reasoning, is characterized by representations that have symbolic and imaginal parts, visual operations that access spatial information contained in the imaginal parts, and visual cases which encode chunks of inferential knowledge. The authors have identified three conditions under which the invocation of quantitative or numerical methods become necessary in order for visual reasoning to proceed. These are described and illustrated by three examples of problem solving that show how quantitative methods get integrated into the framework of visual reasoning
  • Keywords
    inference mechanisms; knowledge representation; spatial reasoning; inference mechanisms; knowledge representation; qualitative methods; quantitative methods; spatial reasoning; visual reasoning; Artificial intelligence; Computational modeling; Geology; History; Humans; Information science; Kinematics; Laboratories; Predictive models; Problem-solving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    AI, Simulation and Planning in High Autonomy Systems, 1991. Integrating Qualitative and Quantitative System Knowledge, Proceedings of the Second Annual Conference on
  • Conference_Location
    Cocoa Beach, FL
  • Print_ISBN
    0-8186-2162-1
  • Type

    conf

  • DOI
    10.1109/AIHAS.1991.138484
  • Filename
    138484