Interoperable Bayesian Agents for Collaborative Learning Environments

摘要

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.