Designers of robotic groups are faced with the formidable task of creating effective coordination architectures that can deal with changing environment conditions and hardware failures. Communication between robots is one mechanism that can at times be helpful in such systems, but can also create a time and energy overhead that reduces performance. In dealing with this issue, various communication schemes have been proposed ranging from centralized and localized algorithms, to non-communicative methods. In this paper we argue that using a coordination cost measure can be useful for selecting the appropriate level of communication within such groups. We show that this measure can be used to create adaptive communication methods that switch between various communication schemes. In extensive experiments in the foraging domain, multi-robot teams that used these adaptive methods were able to significantly increase their productivity, compared to teams that used only one type of communication scheme.