Control of spatially distributed systems is a challenging problem because of their complex nature, nonlinearity, and generally high order. The lack of accurate and computationally efficient model-based techniques for large, spatially distributed systems leads to challenges in controlling the system. Agent-based control structures provide a powerful tool to manago distributed systems by utilizing (organizing) local and global information obtained from the system. A hierarchical, agent-based system with local and global controller agents is developed to control networks of interconnected chemical reactors (CSTRs). The global controller agent dynamically updates local controller agent's objectives as the reactor network conditions change. One challenge posed is control of the spatial distribution of autocatalytic species in a network of reactors hosting multiple species. The multi-agent control system is able to intelligently manipulate the network flow rates such that the desired spatial distribution of species is achieved. Furthermore, the robustness and flexibility of the agent-based control system is illustrated through examples of disturbance rejection and scalability with respect to the size of the network.