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.

El presente trabajo abarca un enfoque alternativo, desde los algoritmos evolutivos, a la manera tradicional en que se abordan los sistemas recomendadores (SR de aquí en adelante). Se examinan las posibilidades de los algoritmos genéticos para brindar características adaptativas a estos sistemas. Nuestro objetivo, además de proporcionar una panorámica informativa general sobre las posibilidades y potencialidades de los SR, es proveer mecanismos para que los SR sean capaces de aprender características personales desde los usuarios, con miras a mejorar la efectividad a la hora de encontrar recomendaciones y sugerencias apropiadas para un individuo en particular.

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.