There is an increasing interest on ensemble learning since it reduces the bias-variance problem of several classifiers. In
this paper we approach an ensemble learning method in a multi-agent environment. Particularly, we use genetic algorithms to
learnt weights in a boosting scenario where several case-based reasoning agents cooperate. In order to deal with the genetic
algorithm results, we propose several multi-criteria decision making methods. We experimentally test the methods proposed
in a breast cancer diagnosis database.
Keywords Ensemble Learning - Case-Based Reasoning - Multi Criteria Decision Making