Drones offer opportunities for networking and control solutions, but also challenges when it comes to their coordination. In this paper, we apply a game theoretic model to multi-agent drone scenarios, to regulate their movement so as to ensure timely positioning but avoiding collisions. Simulations are led through the Nash-Q learning algorithm in order to prove the theoretical analysis and confirm their predicted trajectory dynamics. The results of this work can be exploited as a tool to provide insights for multi-agent control.