New Generation Computing

, Volume 10, Issue 2, pp 223–253 | Cite as

Enhanced qualitative physical reasoning system: Qupras

  • Masaru Ohki
  • Kiyokazu Sakane
  • Jun Sawamoto
  • Yuichi Fujii
Regular Papers


There are many expert systems that use experimental knowledge for diagnostic analysis and design. However, there are two problems for systems using only experiential knowledge:
  1. (1)

    unexpected problems cannot be solved and

  2. (2)

    acquiring experiential knowledge from human experts is difficult.

To solve these problems, general principles or basic knowledge must be added to expert systems in addition to the experimental knowledge. In response, we previously proposed Qupras (Qualitative physical reasoning system) as a framework for basic knowledge. This system has two knowledge representations, one related to physical laws and the other to objects. By using this knowledge, Qupras reasons about the relations among physical objects, and predicts the next state of a physical phenomenon.
Recently, we have improved some of Qupras’ features, and this pater desctibes the following main enhancements:
  1. (1)

    inheritance for representation of objects,

  2. (2)

    new primitive representations to describe discontinuous change, and

  3. (3)

    control features for effective reasoning.



Qualitative Reasoning Knowledge Representation Deep Knowledge Inheritance Discontinuous Change 


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Copyright information

© Ohmsha, Ltd. and Springer 1992

Authors and Affiliations

  • Masaru Ohki
    • 1
  • Kiyokazu Sakane
    • 1
  • Jun Sawamoto
    • 1
  • Yuichi Fujii
    • 1
  1. 1.ICOT Research CenterInstitute for New Generation Computer TechnologyTokyoJapan

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