On a deductive reasoning model and method for uncertainty

Makoto Suzuki, Toshiyasu Matsushima, Shigeichi Hirasawa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    In this paper, we will discuss a problem of deduction with uncertainty that has been dealt with by various diagnostic expert systems. Our two main points are as follows. First, we will propose a mathematical framework of deductive reasoning with uncertainty. Our framework will clarify that a subject of the reasoning is a calculation of conditional probabilities. Second, we will establish a new reasoning method. Our deduction algorithm can compute the conditional probabilities precisely. To put it the other way around, the result minimizes a divergence.

    Original languageEnglish
    Title of host publicationProceedings of the International Conference on Tools with Artificial Intelligence
    PublisherIEEE
    Pages161-164
    Number of pages4
    Publication statusPublished - 1999
    EventProceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence (ICTAI '99) - Chicago, IL, USA
    Duration: 1999 Nov 91999 Nov 11

    Other

    OtherProceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence (ICTAI '99)
    CityChicago, IL, USA
    Period99/11/999/11/11

      Fingerprint

    ASJC Scopus subject areas

    • Software

    Cite this

    Suzuki, M., Matsushima, T., & Hirasawa, S. (1999). On a deductive reasoning model and method for uncertainty. In Proceedings of the International Conference on Tools with Artificial Intelligence (pp. 161-164). IEEE.