MASACAD: A Multi-Agent System for Academic Advising

The evolution of the Internet into the Global Information Infrastructure has led to an explosion in the amount of available information. Realizing the vision of distributed knowledge access in this scenario and its future evolution will need tools to customize the information space. In this article we present MASACAD, a multi-agent system that learns to advise students and discuss important problems in relationship to information customization systems and smooth the way for possible solutions. The main idea is to approach information customization using a multi-agent paradigm.

[1]  Jaideep Srivastava,et al.  Web mining: information and pattern discovery on the World Wide Web , 1997, Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence.

[2]  Mohamed Salah Hamdi.  Extracting and Customizing Information Using Multi-Agents , 2005 .

[3]  Adolfo Guzmán-Arenas,et al.  EVA: an interactive Web-based collaborative learning environment , 2002, Comput. Educ..

[4]  Takahiro Kawamura,et al.  Bee-gent: Bonding and Encapsulation Enhancement Agent framework for development of distributed systems , 1999, Proceedings Sixth Asia Pacific Software Engineering Conference (ASPEC'99) (Cat. No.PR00509).

[5]  Edward A. Feigenbaum,et al.  The Art of Artificial Intelligence: Themes and Case Studies of Knowledge Engineering , 1977, IJCAI.

[6]  Larry Moneta.  The Integration of Technology with the Management of Student Services. , 1997 .

[7]  A. Roli.  Artificial Neural Networks , 2012, Lecture Notes in Computer Science.

[8]  Stephen Grossberg,et al.  Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps , 1992, IEEE Trans. Neural Networks.

[9]  Vice President,et al.  An Introduction to Expert Systems , 1989 .

[10]  Ah-Hwee Tan,et al.  Adaptive resonance associative map , 1995, Neural Networks.

[11]  Raymond J. Mooney,et al.  Symbolic and neural learning algorithms: An experimental comparison , 1991, Machine Learning.

[12]  Peter Jackson,et al.  Introduction to expert systems , 1986 .