| description abstract | Dealing with unforeseeable changing situations, often seen in exploratory and hazardous task domains, requires systems that can adapt to changing tasks and varying environments. The challenge for engineering design researchers and practitioners is how to design such adaptive systems. Taking advantage of the flexibility of multiagent systems, a selforganizing systems approach has been proposed, in which mechanical cells or agents organize themselves as the environment and tasks change based on a set of predefined rules. To enable selforganizing systems to perform more realistic tasks, a twofield framework is introduced to capture task complexity and agent behaviors, and a rulebased social structuring mechanism is proposed to facilitate selforganizing for better performance. Computer simulationbased case studies were carried out to investigate how social structuring among agents, together with the size of agent population, can influence selforganizing system performance in the face of increasing task complexity. The simulation results provide design insights into taskdriven social structures and their effect on the behavior and performance of selforganizing systems. | |
