DocumentCode
2963478
Title
Creating adaptive learning paths using Ant Colony Optimization and Bayesian Networks
Author
Márquez, José Manuel ; Ortega, Juan Antonio ; González-Abril, Luis ; Velasco, Francisco
Author_Institution
R&D Dept., Telvent, Sevilla
fYear
2008
fDate
1-8 June 2008
Firstpage
3834
Lastpage
3839
Abstract
This paper presents a new way to combine two different approaches of artificial intelligence looking for the best path in a graph, ant colony optimization and Bayesian networks. The main objective is to develop a learning management system which will have the capability of adapting the learning path to the learnerpsilas needs in execution time, taking into account the pedagogical weight of each learning unit and the systempsilas social behavior.
Keywords
belief networks; learning (artificial intelligence); optimisation; Bayesian networks; adaptive learning paths; ant colony optimization; artificial intelligence; learning management system; Ant colony optimization; Bayesian methods; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4634349
Filename
4634349
Link To Document