Cascading behavior in infinite networks

The aim of this master thesis is to analyze the underlying mathematical structure of the infinite network models of cascading behavior. Graph theoretical tools are essential to understand the structure of the network and game theoretical tools are employed for the dynamics of the model. It is tried to determine under what conditions on the structure of the graph or on the parameters of the game, cascading is possible. We also consider the optimization problem of choosing the initial set from which cascading behavior spreads through the network. For this purpose, we use the theory of submodular functions. Submodularity condition provides close approximations to the optimal value when the initial set is selected by Greedy Algorithm.