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A qualitative approach to syllogistic reasoning
被引:1
|作者:
Khayata, MY
[1
]
Pacholczyk, D
[1
]
Garcia, L
[1
]
机构:
[1] Univ Angers, LERIA, F-49045 Angers 01, France
关键词:
knowledge representation;
statistical information;
linguistic quantifiers;
quantified assertions;
syllogistic reasoning;
D O I:
10.1023/A:1014425907059
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
In this paper we present a new approach to a symbolic treatment of quantified statements having the following form "Q A's are B's", knowing that A and B are labels denoting sets, and Q is a linguistic quantifier interpreted as a proportion evaluated in a qualitative way. Our model can be viewed as a symbolic generalization of statistical conditional probability notions as well as a symbolic generalization of the classical probabilistic operators. Our approach is founded on a symbolic finite M-valued logic in which the graduation scale of M symbolic quantifiers is translated in terms of truth degrees. Moreover, we propose symbolic inference rules allowing us to manage quantified statements.
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页码:131 / 159
页数:29
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