The OAR model for knowledge representation

被引:0
作者
Wang, Yingxu [1 ]
机构
[1] Univ Calgary, Dept Elect & Comp Engn, Theoret & Empir Software Engn Res Ctr, Calgary, AB T2N 1N4, Canada
来源
2006 Canadian Conference on Electrical and Computer Engineering, Vols 1-5 | 2006年
关键词
cognitive informatics; AI; knowledge representation; OAR; logical model of memory;
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
The cognitive models of information representation and the mechanisms of long-term memory are fundamental research areas in cognitive informatics. This paper develops an Object-Attribute-Relation (OAR) model for describing knowledge and information representation in the brain. According to the OAR model, the human memory and knowledge are represented by relations, i.e. synaptic connections between neurons, rather than by the neurons themselves as the traditional container metaphor described. Based on the OAR model, human knowledge can be formally described as dynamic conjunctions of the existing OAR and the newly identified or generated objects, attributes, and/or relations. The OAR model can be used to explain a wide range of cognitive mechanisms and mental processes in natural and artificial intelligences such as learning, comprehension, and reasoning.
引用
收藏
页码:1988 / 1991
页数:4
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