Agent-based computer systems are surprisingly effective at solving complex problems. Built by combining autonomous computer routines, or agents, with low-bandwidth communication capabilities, these systems typically perform significantly better than the individual routines operating alone. One source of this improvement lies in the cooperative collaboration among the individual agents that compose the system. This work proposes a modular framework for implementing agent-based systems for engineering design. Using a variety of different algorithmic agents, the key ideas are highlighted by identifying multiple identical global optima for a non-convex optimization problem with numerous local minima. The results show that inter- and intra-agent collaboration have a significant impact on system performance. Further, the system can be parallelized with little or no penalty. By observing and analyzing the interactions among individual agents, we gain insights that will aid in the development and management of a conceptual design system for truly hard and large problems. (C) 2003 Published by Elsevier Ltd.