CIM - The hybrid symbolic/connectionist rule-based inference system

被引：0

作者：

Lalitrojwong, P ^{[1
]}

机构：

[1] King Mongkuts Inst Technol Ladkrabang, Fac Informat Technol, Bangkok 10520, Thailand

来源：

INTELLIGENT PROBLEM SOLVING: METHODOLOGIES AND APPROACHES, PRODEEDINGS | 2000年 / 1821卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Previous research has shown that connectionist models are suitable for cognitive and natural language processing tasks. An inference mechanism is a key element in commonsense reasoning in a natural language understanding system. This research project offers a connectionist alternative to Buchheit's symbolic inference module for INFANT called the Connectionist Inference Mechanism (CIM). CIM is a hybrid cognitive model that combines the advantages of the symbolic approach, local representation, and parallel distributed processing. Moreover, it makes good use of its modular structure. Several modules work together in CIM, including memory, neural networks, and a binding set, to perform the inference generation. Besides rule application capability, CIM is also able to perform variable binding. A number of experiments have shown that CIM can make inferences appropriately.

引用

页码：549 / 554

页数：6

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