This paper studies the problem of communication network topology in a multirobot system while the agents are engaged in a given task. The contribution of this paper is to propose a centralized approach to network evolution. In this approach, a communication coordinator is responsible for determining the network topology. The robots periodically send their state information to the communication coordinator. In turn, the communication coordinator considers the individual communication payoff functions of all the robots, their current states and the current network simultaneously and finds a network topology acceptable to all the robots. It models the network topology formation as a pairwise game where it forms or severs pairwise links based on the improvement the resulting network offers the robot pairs relative to the current network. We show that with the assumed form of communication payoff functions, each pairwise game is ensured of convergence to a pairwise stable network. Furthermore, simulation results provide statistical results on the resulting network topology, the number of game moves and the processing time as well as comparative results with the proximity based approach.