Abstract
CBR-Tutor is an Internet agent-based tutoring system that uses Case-Based Reasoning approach in providing adaptive instruction to its learners. The basis for using the Case-Based Reasoning approach is that tutors often learn from their experiences. They can reference to past experience when dealing with students in order for them to know which approach will be appropriate given a situation (or case). CBR-TUTOR is designed as a distributed problem solving architecture where each agent performs decision-making tasks and cooperates to help improve the effectivity of the tutoring system. Each learner has its own tutor agent and tutors don’t only learn from their own experience but they also learn from the experience of other tutoring agents. This paper describes the CBR-Tutor agent components, the agent representation and communication among agents.
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© 2002 Springer-Verlag Berlin Heidelberg
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Reyes, R.L., Sison, R.C. (2002). Agent Representation and Communication in CBR-Tutor. In: Abraham, A., Köppen, M. (eds) Hybrid Information Systems. Advances in Soft Computing, vol 14. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1782-9_33
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DOI: https://doi.org/10.1007/978-3-7908-1782-9_33
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1480-4
Online ISBN: 978-3-7908-1782-9
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