Design Computing and Cognition DCC’14. J.S. Gero (ed), pp. xx-yy. © Springer 2014 1 Dynamic Structuring in Cellular Self-Organizing Systems Newsha Khani and Yan Jin University of Southern California, USA Conventional mechanical systems composed of various modules and parts are of- ten inherently inadequate for dealing with unforeseeable changing situations. Tak- ing advantage of the flexibility of multi-agent systems, a cellular self-organizing (CSO) systems approach has been proposed, in which mechanical cells or agents self-organize themselves as the environment and tasks change based on a set of rules. To enable CSO systems to deal with more realistic tasks, a two-field mech- anism is introduced to describe task and agents complexities and to investigate how social rules among agents can influence CSO system performance with in- creasing task complexity. The simulation results of case studies based on the pro- posed mechanism provide insights into task-driven dynamic structures and their effect on the behavior, and consequently the function, of CSO systems. Introduction Adaptability is needed for systems to operate in harsh and unpredictable environments where it is impossible for the designer to conceptualize eve- ry possible incident and predict details of changing functional require- ments. Space and deep sea explorations and rescue missions in hazardous environments are some examples of such variable environments. In most, if not all, engineered systems, the physical components are designed for a limited purpose and restricted operation range, beyond which the behav- iors are not predictable. The existing approach to dealing with changing task environments re- lies on designers’ imagination of a variety of possible situations of the task domain that helps them devise needed responses to the imaginable possi- bilities. Following the law of requisite variety (Ashby 1956)—i.e., only va- riety (of the system) can conquer variety (of the task)—this approach in-