In this paper, we study the means of developing an imitation process allowing to improve learning in the framework of learning classifier systems. We present three different approaches in the way a behavior observed may be taken into account through a guidance interaction: two approaches using a model of this behavior, and one without modelling. Those approaches are evaluated and compared in different environments when they are applied to three major classifier systems: ZCS, XCS and ACS. Results are analyzed and discussed. They highlight the importance of using a model of the observed behavior to enable an efficient imitation. Moreover, they show the advantages of taking this model into account by a specialized internal action. Finally, they bring new results of comparison between ZCS, XCS and ACS.