This work is focused on the study of the organization of the SEEG signals during epileptic seizures with multi-agent system approach. This approach is based on cooperative mechanisms of auto-organization at the micro level and of emergence of a global function at the macro level. In order to evaluate this approach we propose a distributed collaborative approach for the classification of the interesting signals. This new multi-criteria classification method is able to provide a relevant brain area structures organisation and to bring out epileptogenic networks elements. The method is compared to another classification approach a fuzzy classification and gives better results when applied to SEEG signals.