Mental Imagery Knowledge Representation Mode of Human-Level Intelligence System

  • Authors:

  • Hongdi Ke;Dejiang Zhang;Wen You

  • Affiliations:

  • Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences & Graduate School of Chinese Academy of Sciences, Changchun China 130033 & Jilin Business and Techology Colle ...;Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences & Graduate School of Chinese Academy of Sciences, Changchun China 130033 & Jilin Business and Techology Colle ...;Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences & Graduate School of Chinese Academy of Sciences, Changchun China 130033 & Jilin Business and Techology Colle ...

  • Venue:
  • RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
  • Year:
  • 2009

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Abstract

For the human-level intelligence simulation we should simulate it from the essence of intelligence and with the research results of brain science, cognitive science, artificial intelligence and others. In our study, a mental imagery knowledge representation mode had been established based on cognitive mechanism of human. Two kinds of table named mental imagery concept attributes table and concept attribute value ranges table had been used together to represent mental imagery knowledge in system. Mental imagery concept attributes table which formed by the thought of concept lattice was used to decide relations among concepts and attributes under the circumstance of coarse granularity. While concept attribute value ranges table was used to record differences of individual objects belong to the same concept under the circumstance of fine granularity. The concrete structured method of tables and decision-making process of system were described in the paper. Finally, the validity and feasibility of the knowledge representation mode are illustrated with real examples.