Most physically implemented multi-robot controllers are based on extensions of behavior-based systems. While efficient, such techniques suffer from weak representational power. Symbolic systems, on the other hand, have more sophisticated representations but are computationally complex and difficult to keep synchronized with changes in the environment. In this paper, we describe HIVEMind, a tagged behavior-based architecture for small teams of cooperative robots. In HIVEMind, robots share inferences and sensory data by treating other team members as virtual sensors connected by wireless links. A novel representation based on bitvectors allows team members to share intentional, attentional, and sensory information using relatively lowbandwidth connections. We describe an application of the architecture to the problem of systematic spatial search.