Appointed-time Distributed Nash Equilibrium Seeking for Networked Games

Distributed Nash Equilibrium (NE) seeking for networked games has been widely investigated in recent years. In particular, convergence speed and communication cost are two of the critical concerns for the design of the seeking algorithms. To achieve fast convergence while saving communication resources, this paper investigates the appointed-time distributed NE seeking problem for networked games under a discrete-time communication scenario. By utilizing the idea of motion planning, a new continuous-time distributed NE seeking algorithm, which ensures convergence to NE at the prescribed time, is proposed based on sampled-data information exchange. Compared with the existing related works, the established algorithm has advantages on both the communication cost and convergence speed (i.e., appointed-time convergence). Finally, the effectiveness of the proposed method is verified via numerical simulations.