Network games consist of a set of agents, each playing a strategy against its neighbors. After a while, some network games will settle in a state where no agent wants to change its strategy. At that point, we say that the network has converged to an equilibrium.

In this project, we will consider a special type of dynamics, where if the number of agents playing a specific strategy increases; other agents will be more inclined to choose it. (For example, fashion trends behave this way.)

We try to prove conditions for the convergence of these networks and also come up with efficient ways to control the equilibrium. In other words, we would like for all agents to play a specific strategy in the equilibrium. And to that end, we offer agents payoff incentives. Based on the previous results, we propose algorithms to choose the agents that are going to receive incentives, in a way that optimizes the total amount we have to offer to control the network.