• DocumentCode
    2467843
  • Title

    Knowledge mediator Decomposing expert agent knowledge to develop novice agent knowledge comprehension

  • Author

    Nurmaya ; Kwon, Gyu Hyun

  • Author_Institution
    Center for Bionics, Korea Inst. of Sci. & Technol., Seoul, South Korea
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    1153
  • Lastpage
    1158
  • Abstract
    As humans have different levels of expertise, this differentiation becomes one of the obstacles to the construction of knowledge comprehension by exchanging knowledge. To overcome this problem, we decompose experts´ knowledge presentation while aiming to build knowledge comprehension in novice agents using concept maps as a knowledge representation of multiplication problems. The proposed collaborative interaction model is a mediator of communication built by CLARION. This collaborative interaction model may be a solution to overcome the problems which arise when building group collaboration systems for learning purposes.
  • Keywords
    knowledge representation; learning (artificial intelligence); multi-agent systems; CLARION; collaborative interaction model; concept map; expert agent knowledge decomposition; group collaboration system; knowledge mediator; knowledge representation; learning purpose; multiplication problem; novice agent knowledge comprehension; Adaptation models; Cognitive science; Collaboration; Educational institutions; Humans; Interviews; CLARION; Collaborative Interaction; Concept Maps; Levels of Expertise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6377887
  • Filename
    6377887