In this paper, we introduce a new approach to autonomous decentralized shop floor routing. Our system, which we call Ant Colony Control (AC 2), applies the analogy of a colony of ants foraging for food to the problem of dynamic shop floor routing. In this system, artificial ants use only indirect communication to make all shop routing decisions by altering and reacting to their dynamically changing common environment through the use of simulated pheromone trails. For simple factory layouts, we show that the emergent behavior of the colony is comparable to using the optimal routing strategy. Furthermore, as the complexity of the factory layout is increased, we show that the adaptive behavior of AC 2 evolves local decision making policies that lead to near-optimal solutions from the standpoint of global performance.