In multi-agent systems with self-interested individuals interacting locally, it can be difficult to determine if cooperative behavior will emerge. Evolutionary Game Theory provides some valuable tools to this end, but is not suited to systems with dynamic models of interaction. Mobile ad hoc networks provide a compelling application for evolutionary game theory, but there are still significant gaps between the theoretical results and the practical challenges. We discuss and provide some of the assumptions necessary to apply previous work in evolutionary game theory to the ad hoc network packet routing domain. We then analyze the similarities and differences between Brownian mobility and Random Waypoint mobility and show that convergence to cooperation requires a significant reduction in velocity for the Random Waypoint model. Our contribution is to provide evidence that more realistic mobility models can make convergence to cooperation more difficult than previously shown using random methods.