Nash equilibrium computation of two-network zero-sum games with event-triggered communication

In this paper, a zero-sum game Nash equilibrium computation problem with event-triggered communication is investigated under an undirected weight-balanced multi-agent network. A novel distributed event-triggered projection subgradient algorithm is developed to reduce the communication burden within the subnetworks. In the proposed algorithm, when the difference between the current state of the agent and the state of the last trigger time exceeds a given threshold, the agent will be triggered to communicate with its neighbours. Moreover, we prove that all agents converge to Nash equilibrium by the proposed algorithm. Finally, two simulation examples verify that our algorithm not only reduces the communication burden but also ensures that the convergence speed and accuracy are close to that of the time-triggered method under the appropriate threshold.