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Risk-based regulation has grown rapidly as a component of Government decision making, and as such, the need for an established evidence-based framework for decisions about risk has become the new mantra. However, the process of brokering scientific evidence is poorly understood and there is a need to improve the transparency of this brokering process and decisions made. This thesis attempts to achieve this by using agent-based simulation to model the influence that power structures and participating personalities has on the brokering of evidence and thereby the confidence-building exercise that characterises risk-based regulation. As a prerequisite to the adoption of agent-based techniques for simulating decisions under uncertainty, this thesis provides a critical review of the influence power structure and personality have on the brokering of scientific evidence that informs risk decisions. Three case studies, each representing a different perspective on risk-based regulation are presented: nuclear waste disposal, the disposal of avian-influenza infected animal carcases and the reduction of dietary salt intake. Semi-structured interviews were conducted with an expert from each case study, and the logical sequence in which decisions were made was mapped out and used to inform the development of an agent-based simulation model. The developed agent-based model was designed to capture the character of the brokering process by transparently setting out how evidence is transmitted from the provider of evidence to the final decision maker. It comprises of two agents, a recipient and provider of evidence, and draws upon a historic knowledge base to permit the user to vary components of the interacting agents and of the decision-making procedure, demonstrating the influence that power structure and personality has on agent receptivity and the confidence attached to a number of different lines of evidence. This is a novel step forward because it goes beyond the scope of current risk management frameworks, for example, permitting the user to explore the influence that participants have in weighing and strengthening different lines of evidence and the impact this has on the final decision outcome.