A multi-agent architecture for an ITS with multiple strategies

  • Thierry Mengelle
  • Claude Frasson
Learning Environments: Modelling and Design
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1108)


This research aims to implement an intelligent tutoring system with multiple co-operative strategies involving several pedagogical agents (for instance: tutor, co-tutor, companion, ...). Such agents are able to play different pedagogical roles, consequently, we called them actors. We describe a general architecture for actors, and illustrate it in the context of a new strategy: learning by disturbing. A prototype of an environment for building actors has been implemented using an object oriented language; it allows to develop new co-operative pedagogical strategies.


Control Task Intelligent Agent Typical Situation Multiple Strategy Intelligent Tutor System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Aïmeur, E., Frasson, C., Stiharu-Alexe, C.: Towards New Learning Strategies In Intelligent Tutoring Systems, Brazilian Conference of Artificial Intelligence SBIA'95 (1995) 121–130Google Scholar
  2. 2.
    Aïmeur, E., Frasson, C.: Analyzing a new learning strategy according to different knowledge levels, Computer and Education, An International Journal (1996), to appearGoogle Scholar
  3. 3.
    Chan, T.W., Baskin, A.B.: Learning Companion Systems. In C. Frasson & G. Gauthier (Eds.), Intelligent Tutoring Systems: At the Crossroads of Artificial Intelligence and Education, Chapter 1, New Jersey, Ablex Publishing Corporation (1990)Google Scholar
  4. 4.
    Frasson C., Mengelle T., Aïmeur E., Gouardères G.: An Actor-Based Architecture for Intelligent Tutoring Systems. Third International Conference ITS'96, Montréal. Canada, LNCS (1996), to appear.Google Scholar
  5. 5.
    Gilmore, D., Self, J.: The application of machine learning to intelligent tutoring systems. In J. Self (Ed.), Artificial Intelligence and Human Learning, Intelligent computer-assisted instruction, New York: Chapman and Hall (1988) 179–196Google Scholar
  6. 6.
    Huffman, S. B., Laird, J.E.: Flexibly Instructable Agents, Journal of Artificial Intelligence Research, Volume 3 (1995) 271–324Google Scholar
  7. 7.
    Mengelle, T.: Etude d'une architecture d'environnements d'apprentissage basés sur le concept de préceptorat avisé. PhD Thesis, University of Toulouse III (1995)Google Scholar
  8. 8.
    Morignot P., Hayes-Roth, B.: Why does an agent act ? In M.T. Cox & M. Freed (Eds.), Proceedings of the AAAI Spring Symposium on Representing Mental States Mechanisms. Menlo Park, AAAI (1995)Google Scholar
  9. 9.
    Nkambou, R., Lefebvre, B., Gauthier, G.: A Curriculum-Based Student Model for Intelligent Tutoring System. Fifth International Conference on User Modelling, Kailua-Kona (1996) 91–98Google Scholar
  10. 10.
    Palthepu, S., Greer, J., McCalla, G.: Learning by Teaching. The Proceedings of the International Conference on the Learning Sciences, AACE (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Thierry Mengelle
    • 1
  • Claude Frasson
    • 1
  1. 1.Département d'informatique et de recherche opérationnelleUniversité de MontréalMontréalCanada

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