ABSTRACT
Recent studies of nonlinear and open systems have led to the understanding of cities as evolutionary and complex systems (Allen 1997). Cities are looked at as self-organising systems, which are remarkably suited to computational simulation (Clarke and Gaydos 1998; Wolfram 1984). A cellular automaton is characterised by phase transitions that can generate complex patterns through simple transition rules. As such, this technique seems ideally suited to modelling the complexity of urban systems (Clarke and Gaydos 1998; Batty 1995). In this chapter, the principles of cellular automata simulation are discussed, and the applications of this simulation technique in modelling urban development are reviewed. Through this review, the progress and limitations of the cellular automata for urban development modelling are identified, leading to the development of a fuzzy constrained cellular automata model of urban development in the following chapters.
