A city is a pattern in time. The city persists, while no single constituent remains in place, or rather because it is in constant flux. Much like any living system, a city must change in order to maintain its integrity and its identity. Coherence under change is a common characteristic of complex adaptive systems (Holland, 1995). Though the activity of an individual actor in a city can be complex, the behavior of the aggregate identity of a city is more complex than the sum of these individual activities. Thus, the city's behavior depends on the interactions much more than on the actions. Complexity theory involves the study of many actors and their interactions. Large-scale effects of locally interacting agents are called 'emergent properties' of the system. Emergent properties can be deduced in some models, such as neoclassical economic models in which rational agents operate under strong assumptions about the availability of information. Although people may try to be rational, they rarely can meet the requirements of information or foresight that rational models impose. The main alternative to the assumption of rational choice is some form of adaptive behavior. The consequences of adaptive processes are often very hard to deduce when there are many interacting agents following rules that have nonlinear effects. Because the study of large numbers of actors with changing patterns of interactions often is too difficult for a mathematical solution, a primary research tool of complexity theory is computer simulation.