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

  • Authors:
  • Yingxu Wang;Guenther Ruhe;Marina L. Gavrilova;Yousheng Tian

  • Affiliations:
  • University of Calgary, Canada;University of Calgary, Canada;University of Calgary, Canada;University of Calgary, Canada

  • Venue:
  • International Journal of Software Science and Computational Intelligence
  • Year:
  • 2011

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Abstract

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.