This paper presents a view of cooperative control using the language of learning in games. We review the game theoretic concepts of potential games and weakly acyclic games and demonstrate how the specific cooperative control problem of consensus can be formulated in these settings. Motivated by this connection, we build upon game theoretic concepts to better accommodate a broader class of cooperative control problems. In particular, we introduce sometimes weakly acyclic games for time-varying objective functions and action sets, and provide distributed algorithms for convergence to an equilibrium. Finally, we illustrate how to implement these algorithms for the consensus problem in a variety of settings, most notably, in an environment with non-convex obstructions.