Bayesian decision support in complex modular systems : an algebraic and graphical approach
Manuele Leonelli · Warwick Research Archive Portal (University of Warwick) · 2015
Nowadays decision centres are required to make choices in complex and evolving environments, described through multiple and interdependent processes with many associated measurements. The objective of a real time decision making centre is to agree to a sequence of efficacious countermeasures. To achieve this it is usually necessary to integrate opinions and information from an often diverse set of stakeholders, articulating several competing objectives and knowledge over different domains of expertise. A collection of decision support systems can enhance such an integration, not only ensuring that all relevant evidence systematically informs policy making, but also encouraging the decision centre to exhibit an underlying consistency across all its components and to address the problem as a whole. In this thesis we develop a formal framework, extending standard Bayesian methodology, enabling the judgements and the models of groups of experts to be coherently aggregated in a unique entity. We discuss when and how it is possible to do so and the conditions the group needs to agree upon. We call this framework integrating decision support system. We then develop a variety of methodologies to enhance such an integration, enabling integrating decision support systems to be feasibly used in practice.