Adaptation and Optimisation of Pedagogical Paths by Ants´s Algorithm

This paper describes an approach of optimisation and adaptation of the pedagogical path of a learner. This optimisation is inspired of a field of artificial intelligence: ant colony optimisation (ACO) (Bonabeau et al., 1999; Bonabeau et al., 2000; Resnick, 1994). The structure of the e-learning material is represented by a graph with valued arcs whose weights are optimised by virtual ants (learners) that release virtual pheromones along their paths (learner´s performances). This gradual modification of the graph´s structure improves its pedagogic pertinence in order to increase pedagogic success. In this paper, the first section introduces adaptive hypermedia systems and their general architecture. The next section describes our approach based on (ACO) in order to adapt the pedagogical paths in our system. In the end, an implementation of our model is presented