On the design of tele-learning systems using genetic algorithms

A tele-learning system may be modeled using an object-oriented approach which lends to eventual simulation using object-oriented languages. In this study, the human users of the system are included as system components with their own respective characteristics, as described by such descriptive social-economic parameters as user satisfaction, user willingness to pay, and others. The current focus of the study is on the genesis of tele-learning systems, that is, a specification of fundamental descriptive parameters, somewhat akin to genes in genetics, that may be encoded as binary strings, and of a fitness function of these parameters which is to be optimized using genetic algorithms. The fitness function measures some critical aspects of the system´s behaviour of interest to the system designer. The strings corresponding to the optimal value of this function then will specify an optimal system design