• DocumentCode
    2799536
  • Title

    Exploiting Model of Personality and Emotion of Learning Companion Agent

  • Author

    Li, Taihua ; Qiu, Yuhui ; Yue, Peng ; Zhong, Guoxiang

  • Author_Institution
    Southwest Univ., Chongqing
  • fYear
    2007
  • fDate
    13-16 May 2007
  • Firstpage
    860
  • Lastpage
    865
  • Abstract
    In the development and application of intelligent learning environments, an important trend is to integrate characteristics proper of human, such as personality and emotion, into the intelligent interface agents, with the aim of providing the student with a more personalized and friendly environment. The learning companion is a kind of very useful intelligent interface agent in the learning environment. Therefore, exploring the model of personality and emotion of learning companion agent is the crucial problem to make it more hominine and believable. In this paper, the related works on personality and emotions in psychology and artificial intelligence are reviewed briefly, and a framework of learning companion agent with Personality and Emotions is proposed. Based on the OCEAN model and the OCC model, the model of personality and emotion of learning companion agent is defined and formalized. Moreover, the computation and the coming implementation of the model are described in detail.
  • Keywords
    learning (artificial intelligence); psychology; OCC model; OCEAN model; emotion; intelligent interface agent; intelligent learning; learning companion agent; personality; psychology; Application software; Artificial intelligence; Biological system modeling; Educational institutions; Humans; Intelligent agent; Learning; Oceans; Psychology; Software engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications, 2007. AICCSA '07. IEEE/ACS International Conference on
  • Conference_Location
    Amman
  • Print_ISBN
    1-4244-1030-4
  • Electronic_ISBN
    1-4244-1031-2
  • Type

    conf

  • DOI
    10.1109/AICCSA.2007.370733
  • Filename
    4231061