tomata modelling, like opinion formation or neighbourhood segregation. However, to our knowledge there are virtually no insights into how regular vs. irregular grid structures affect cellular dynamics [14]. Cellular Automata extensions using Voronoi spatial models have been previously proposed to overcome this problem. In these approaches one uses convex cells with different sizes and shapes that can provide a much more adequate terrain partition. A different problem lies in the fact that, on regular Cellular Automata, each cell has a finite set of possible states, and transition between states is a crisp function of present cell state and neighbour cells state. Crisp data modelling and crisp transition mechanisms have known limitations when one trying to model and simulate real-world processes where uncertainty and imprecision is present and cannot simply be ignored [28]. The most prominent reason is that Cellular Automata can be seen as multi-agent system based on locality with overlapping interaction structures. In this perspective, Cellular Automata is attractive as a modelling framework that may provide a better understanding of micro/macro relations. We will give some background specific to the study of cellular automata, and then background from other fields that are necessary for the work here [17]. We will then conclude with some potential questions that merit future investigation, and where appropriate we will discuss potential consequences of such questions.

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