A Formal Knowledge Representation System (FKRS) for the Intelligent Knowledge Base of a Cognitive Learning Engine

Author(s):  
Yousheng Tian ◽  
Yingxu Wang ◽  
Marina L. Gavrilova ◽  
Guenther Ruhe

It is recognized that the generic form of machine learning is a knowledge acquisition and manipulation process mimicking the brain. Therefore, knowledge representation as a dynamic concept network is centric in the design and implementation of the intelligent knowledge base of a Cognitive Learning Engine (CLE). This paper presents a Formal Knowledge Representation System (FKRS) for autonomous concept formation and manipulation based on concept algebra. The Object-Attribute-Relation (OAR) model for knowledge representation is adopted in the design of FKRS. The conceptual model, architectural model, and behavioral models of the FKRS system is formally designed and specified in Real-Time Process Algebra (RTPA). The FKRS system is implemented in Java as a core component towards the development of the CLE and other knowledge-based systems in cognitive computing and computational intelligence.

Author(s):  
Yousheng Tian ◽  
Yingxu Wang ◽  
Marina L. Gavrilova ◽  
Guenther Ruhe

It is recognized that the generic form of machine learning is a knowledge acquisition and manipulation process mimicking the brain. Therefore, knowledge representation as a dynamic concept network is centric in the design and implementation of the intelligent knowledge base of a Cognitive Learning Engine (CLE). This paper presents a Formal Knowledge Representation System (FKRS) for autonomous concept formation and manipulation based on concept algebra. The Object-Attribute-Relation (OAR) model for knowledge representation is adopted in the design of FKRS. The conceptual model, architectural model, and behavioral models of the FKRS system is formally designed and specified in Real-Time Process Algebra (RTPA). The FKRS system is implemented in Java as a core component towards the development of the CLE and other knowledge-based systems in cognitive computing and computational intelligence.


2012 ◽  
Vol 472-475 ◽  
pp. 2320-2324
Author(s):  
Jun Liang He ◽  
Wei Min Zhang ◽  
Wei Yan ◽  
Zhan Min Lv

Firstly, this paper put forward knowledge acquisition and knowledge organization from the yard plans through KSP. Furthermore, the paper explores the approach of the construction of Production knowledge representation system. Finally, the effectiveness and reliability of the knowledge-based berth and quay crane assignment has been verified by the case studies conducted.


1987 ◽  
Author(s):  
Marinette Revenu ◽  
Christine Porquet ◽  
Jean-Yves Leannec ◽  
Felix Cuozzo

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