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Anthropology, and other disciplines have searched for isomorphic principles and rules operating in information systems. This thesis locates and describes this deep structure applicable to all information systems. It presents a model for information flow as a set of ordering principles revealing universal patterns inherent in nature, a set of transformation rules functioning to increase organization and complexity, and a structure for this activity. The model is isomorphic: it demonstrates similar operational behavior in different systems. Major features of the model include polarity, emergent or transformational phenomena, self-organization, and a trajectory traveling through a hierarchical structure representing the flow of information. Polar opposition is the primary functional mechanism, and has two critical roles. It initiates and maintains the trajectory through time and stabilizes the system by representing existence in time. The author applies the model to consciousness, neurogenesis, ontogeny, social behavior, mythology, rites of passage, and other systems. / Department of Anthropology

M.Sc. (Information Technology) / Making changes to a complex system, such as a cellular network, without being well informed about the potential effects of the change could prove to have negative and costly outcomes. In order to diminish the risk of making changes to a real system, a simulation of the real system is a viable and valuable alternative. By creating a simulation of the real system, the effects of changes made can be tested in the simulation instead of the real system. The dissertation presents a model by which subscriber behaviour within a cellular network can be simulated. The model that is introduced to this end is called the Mobile Network Subscriber-Behaviour Simulation (MNSS). Subscriber behaviour is important as it is largely responsible for the variation in traffic within the cellular network. Thus, the research presented in the dissertation seeks to provide a means by which the planning and operation of cellular networks can be enhanced through a better comprehension of network traffic, which is influenced by subscriber behaviour. In the dissertation, specific focus is given to voice traffic, and, as such, the cellular network architecture that was chosen for the model is the GSM mobile network architecture due to its ubiquitous use in carrying voice traffic. The research presented in the dissertation begins with a discussion on the GSM architecture. Subscriber behaviour is simulated through the use of intelligent agents that are configured to interact with one another to form a Multi-agent System. In addition, the subscriber agents interact with, and adapt to, the mobile network component of the MNSS model, which constitutes the formation of a Complex Adaptive System. Therefore, the discussion is subsequently directed towards Artificial Intelligence, intelligent agents, Multi-agent Systems and Complex Adaptive Systems. Using these aforementioned concepts, the dissertation presents the MNSS model and a prototype implementation, as well as a discussion on the results obtained from this. The main purpose of the dissertation is to examine a means by which subscriber behaviour can be simulated in a cellular network, through the use of multiple intelligent agents that interact in a complex system. This is conducted for the express purpose of analysing the change in behaviour of the subscriber agents in relation to changes made to external conditions, such as the underlying cellular network or the behaviour of other subscriber agents.