We have developed a novel architecture for agents in colonies, in order to investigate certain forms of group interaction. Specifically, we are interested in the extent to which overall goals for a colony can be achieved when each agent is only aware of limited local goals, whether the architecture allows for emergence of unexpected behavior, and whether explicit communication among agents facilitates or hinders task performance. Our architecture supports several forms of learning. We have studied large colonies of agents (as many as 100) in simulation experiments, where they carried out fetch-and-carry tasks in the presence of predators and with limited energy reserves. In addition, we have fabricated a physical colony of four agents, with the same architecture, to insure that the behaviors we observed in simulation were also present in the hardware implementations.