This brief talk aims to show how the stochastic differential games contribute to the optimal solution of large-scale engineering problems emerging in smart cities where several dynamical interactions occur, e.g., the water distribution system, the crowd management, the traffic flow, power systems, among many others. We show that the general simplest problem statement leads to a complex PIDE system involving a backward Hamilton-Jacobi-Bellman equation coupled with a forward Fokker-Plank-Kolmogorov equation. Then, we discuss how this complexity can be handled for specific cases pursuing to develop real implementation. As an example, we focus on the crowd evacuation problem. Finally, future directions we are currently working on involving machine learning and stability are presented.
This video was produced by the SITE Research Center at New York University, as part of their talk series.
