“space syntax theory” such as Hillier [@hillier1976space], the field is very broad and diverse. Yet, all these works share the view that urban systems are quintessentially *complex systems*, i.e. large sets of elements interacting locally with one another and the environment, and collectively creating a emergent structure and behavior. Taking into account the intrinsic *heterogeneity* of geographical and urban systems, this view lends itself naturally to an agent-based modeling and simulation (ABMS) approach.

Among the most popular ABMS methods are cellular automata (CA), in which agents are cells that have fixed locations on a grid and evolve according to the state of their neighbors. CA models of urban planning, in particular the reproduction of existing urban forms and land-use patterns, have been widely studied, notably by White and Engelen [@white1993cellular], then analyzed [@batty1997cellular; @batty1997possible] and synthesized [@Bat07] by Batty. A recent review by Iltanen [@iltanen2012cellular] of CA in urban spatial modeling shows a great variety of possible system types and applications. They include, for example, “microeconomic” CA for the simulation of urban sprawl [@DBM11], “linguistic” CA (including real-time rule update via feedback from the population) for the measure of sustainable development in a fast growing region of China [@Wu96alinguistic], and 