The goal in networked control of multiagent systems is to derive desirable collective behavior through the design of local control algorithms. The information available to the individual agents, either through sensing or communication, invariably defines the space of admissible control laws. Hence, informational restrictions impose constraints on the achievable performance guarantees. The first part of this talk will provide one such constraint with regards to the efficiency of the resulting stable solutions for a class of networked coverage problems. In particular, Marden will demonstrate that there is an inherent tension between the price of anarchy and price of stability, which are two worst-case measures on the performance of the best and worst equilibrium in a given system, when restricting attention to designs where the agents make independent decisions using only information about their local environment. He will then demonstrate that one can move beyond this frontier when a minimal degree of system-level information is shared between the agents. The last part of this talk will present some preliminary results on the impact of information in submodular optimization problems.