This WP will be concerned with conducting a careful review of existing methods for the control of multi-agent systems based on the use of machine learning techniques and the definition of appropriate metrics to assess their performance from a control and data efficiency viewpoint. The aim will be the identification of the key strategies presented in the literature to be used in the rest of the project to benchmark the proposed strategies. BO will implement and evaluate all the strategies numerically through simulations, while NA will focus on all the control related aspects so as to merge expertise from both teams to achieve a full characterization and classification of the available strategies.