On a deductive reasoning model and method for uncertainty

Makoto Suzuki, Toshiyasu Matsushima, Shigeichi Hirasawa

Research output: Contribution to journalConference article

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
Pages (from-to)161-164
Number of pages4
JournalProceedings of the International Conference on Tools with Artificial Intelligence
Publication statusPublished - 1999 Dec 1
EventProceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence (ICTAI '99) - Chicago, IL, USA
Duration: 1999 Nov 91999 Nov 11

ASJC Scopus subject areas

  • Software

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