This work presents an alternative approach (Evolutionary Algorithms approach) to traditional treatment of Recommender Systems (RSs). The work examines genetic algorithms possibilities to offer adaptive characteristics to this systems trough learning. The main goal, in addition to give a general view about RSs capabilities and possibilities, it is to provide an example mechanism for to extend RSs learning capabilities (from users´s personal chracteristics), with the purpose to improve the effectiveness in the moment of to find recommendations and appropriate suggestions for particular individuals.

This paper is about the decisión analysis methods for group decisions over the web, in reason of involve the people in the different decisions that interest them, we have in internet one chance for to reduce the gap between governor and governed We can summarize the main object that pursues this like to propose one automated negotiation approach in the web, which be based on the evolutionary computation and the game theory.

This work presents an alternative approach (Evolutionary Algorithms approach) to traditional treatment of Recommender Systems (RSs). The work examines genetic algorithms possibilities to offer adaptive characteristics to this systems trough learning. The main goal, in addition to give a general view about RSs capabilities and possibilities, it is to provide an example mechanism for to extend RSs learning capabilities (from users´s personal chracteristics), with the purpose to improve the effectiveness in the moment of to find recommendations and appropriate suggestions for particular individuals.

This paper is about the decisión analysis methods for group decisions over the web, in reason of involve the people in the different decisions that interest them, we have in internet one chance for to reduce the gap between governor and governed We can summarize the main object that pursues this like to propose one automated negotiation approach in the web, which be based on the evolutionary computation and the game theory.