TY - JOUR
T1 - On a deductive reasoning model and method for uncertainty
AU - Suzuki, Makoto
AU - Matsushima, Toshiyasu
AU - Hirasawa, Shigeichi
PY - 1999
Y1 - 1999
N2 - 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.
AB - 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.
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M3 - Conference article
AN - SCOPUS:0033313687
SN - 1063-6730
SP - 161
EP - 164
JO - Proceedings of the International Conference on Tools with Artificial Intelligence
JF - Proceedings of the International Conference on Tools with Artificial Intelligence
T2 - Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence (ICTAI '99)
Y2 - 9 November 1999 through 11 November 1999
ER -