Cellular automata and political information

This study examines cellular automata as a method of modelling the movement of information through a political system. Cellular automata systems provide a discrete time space model which allows the researcher considerable flexibility in specifying the characteristics of the political agents within the system as well as specifying the nature of the interactions between agents and with the system. Cellular automata (CA) are a part of the general class of dynamical systems. CA systems link discretized spatial elements called cells that communicate with the system through the context of local neighborhoods which operate in discrete, though not necessarily synchronous time. As a dynamical system, the rule is part of a feedback mechanism which calculates the next value of every cell with each iteration.; Information theory is also studied to understand the measurement of information within a system. Shannon's channel model of communications theory is reviewed and the components of a message are analyzed. Shannon's measure of the amount of information in a message, called entropy, is employed in this study as the primary measure of information content within the system. Entropy can be calculated in time and/or space, thus giving the researcher significant latitude in the investigation of the system.; Experiments are conducted to analyze system behavior and information flow under five groups of rules in a simple cellular automata model. The experimental results generally demonstrate similar behavior within groups, although unexpected forms of behavior are noted. These experiments provide evidence that cellular automata systems are an excellent modelling tool to further the study of political behavior. While predominantly used in the physical and life sciences, the social sciences are beginning to appreciate the capacity of CA to model complex systems.