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Interoperable Bayesian Agents for Collaborative Learning Environments

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Current Topics in Artificial Intelligence (CAEPIA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4788))

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Abstract

Collaborative work can be supported by many tools and it has been included in a large number of learning environments design. This paper presents issues related to an educational portal design and collaboration in Intelligent Tutoring Systems (ITS). In order to achieve the collaboration it was necessary to provide a way to interoperate knowledge among the heterogeneous systems. We have been developing ITS as resources to improve the individual and personalized learning. We believe that individual experiences can be more successful when the student has more autonomy and he is less dependent of the professor. In this research direction, this paper details the Social Agent reasoning, an agent to improve student’s learning stimulating his interaction with other students, and how this agent exchange bayesian knowledge among AMPLIA agents. The AMPLIA environment is an Intelligent Probabilistic Multi-agent Environment to support the diagnostic reasoning development and the diagnostic hypotheses modeling of domains with complex and uncertain knowledge, like medical area.

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References

  1. Nakayama, L., Vicari, R.M., Coelho, H.: An information retrieving service for distance learning. Transactions on Internet Research 1(1), 49–56 (2005)

    Google Scholar 

  2. Vicari, R.M., Flores, C.D., Silvestre, A.M., Seixas, L.J., Ladeira, M., Coelho, H.: A multi-agent intelligent environment for medical knowledge. Artificial Intelligence in Medicine 27(3), 335–366 (2003)

    Article  Google Scholar 

  3. The Foundation for Intelligent Physical Agents: Specifications (2006), Available from http://www.fipa.org

  4. Castelfranchi, C., Rosis, F., de Falcone, R.: Social Attitudes and Personalities in Agents, Socially Intelligent Agents. In: AAAI Fall Symposium (1997)

    Google Scholar 

  5. Prada, R., Paiva, A.: Believable Groups of Synthetic Characters. In: AAMAS 2005 (July 25-29, 2005)

    Google Scholar 

  6. Jaques, P.A., Viccari, R.M.: A BDI Approach to Infer Student’s Emotions in an Intelligent Learning Environment, Computers and Education, England (2005)

    Google Scholar 

  7. Conati, C.: Probabilistic assessment of user’s emotions in educational games. Journal of Applied Artificial Intelligence 16(7-8), 555–575 (2002)

    Article  Google Scholar 

  8. Cheng, R., Vassileva, J.: Adaptive Reward Mechanism for Sustainable Online Learning Community. In: AI in Education (AIED) 2005, July 18-22, pp. 152–159. IOS Press, Amsterdam (2005)

    Google Scholar 

  9. Ding, Z., Peng, Y.: A probabilistic extension to ontology language OWL. In: Hawaii International Conference On System Sciences (2004)

    Google Scholar 

  10. Gluz, J.C., Flores, C.D., Seixas, L., Vicari, R.M.: Formal analysis of a probabilistic knowledge communication framework. In: IBERAMIA/SBIA Joint Conference (2006)

    Google Scholar 

  11. Boff, E., Santos, E.R., Vicari, R.M.: Social agents to improve collaboration on an educational portal. In: IEEE International Conference on Advanced Learning Technologies, pp. 896–900. IEEE Computer Society Press, Los Alamitos (2006)

    Chapter  Google Scholar 

  12. Piaget, J.: Explanation in sociology, Sociological studies. Routledge, New York (1995)

    Google Scholar 

  13. Vygotsky, L.S.: The collected works of L.S. Vygotsky, vol. 1–6, pp. c1987–c1999. Plenum Press, New York

    Google Scholar 

  14. Ortony, A., Clore, G.L., Collins, A.: The cognitive structure of emotions. Cambridge University Press, Cambridge (1988)

    Google Scholar 

  15. Dean, M., Schreiber, G.: OWL Web Ontology Language Reference, Technical report, W3C (February 2004)

    Google Scholar 

  16. Santos, E.R., Fagundes, M., Vicari, R.M.: An Ontology-Based Approach to Interoperability for Bayesian Agents. In: International Conference on Autonomous Agents and Multiagent Systems, 2007, Honolulu. Proceedings of AAMAS (2007)

    Google Scholar 

  17. Stanford University, The Protégé Ontology Editor and Knowledge Acquisition System, Available from http://protege.stanford.edu

  18. Carroll, J.J., Dickinson, I., Dollin, C., Reynolds, D., Seaborne, A., Wilkinson, K.: Jena: Implementing the semantic web recommendations, Technical Report, Hewlett Packard Laboratories (2003)

    Google Scholar 

  19. Bellifemine, F., Poggi, A., Rimassa, G.: JADE – A FIPA-compliant agent framework. In: 4th International Conference and Exhibition on The Practical Application of Intelligent Agents and Multi-Agent Technology, pp. 97–108 (1999)

    Google Scholar 

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Daniel Borrajo Luis Castillo Juan Manuel Corchado

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Boff, E., Santos, E.R., Fagundes, M.S., Vicari, R.M. (2007). Interoperable Bayesian Agents for Collaborative Learning Environments. In: Borrajo, D., Castillo, L., Corchado, J.M. (eds) Current Topics in Artificial Intelligence. CAEPIA 2007. Lecture Notes in Computer Science(), vol 4788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75271-4_4

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  • DOI: https://doi.org/10.1007/978-3-540-75271-4_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75270-7

  • Online ISBN: 978-3-540-75271-4

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