Modeling of e-Learning Based on Ant Colony Algorithm
E-learning and distance education via the Internet is a means of current and promising teaching. However, it suffers from defects mainly related to the relative absence of the teacher and, therefore, the difficulty of adapting teaching to the level and behavior of the learner. This paper describes an approach of modeling and adaptation of the e-learning. This modeling is based on the Ant Colony Optimization (ACO). In the authors' modeling, e-learning is schematized by a graph where nodes represent the educational elements (lessons or exercises), and arcs link navigation between them. Each of the arcs is also a value that describes its importance in relation to teaching neighboring arcs. Students are represented by virtual agents (ants) who use these links.