AbstractAs technology evolves, new methods for supporting individuals emerge and the way that experts tackle problems changes. Over the past two decades a major focus of technological improvements within industry has been to automate large parts of the workforce and reduce the number of workers. In recent years however global industrial policy has started shifting towards empowering individuals with technology instead. This presents a major drive for research in the development of new technologies that will support professional individuals in making informed decisions.
The objective of this research is to develop a new theoretical model for a Decision Support System in the form of a Virtual Personal Assistant that supports professional individuals in exploring ambiguous and uncertain problem spaces. This thesis presents the hypothesis that intelligent agents with learning capabilities that develop personalised relationships with professional individual users can deliver contextually relevant benefits by supporting the user’s decision making process. The contribution of this research is a viable model of a Decision Support System that describes an intelligent agent that provides contextually relevant support to unique users when facing ambiguity in decision making. This is supported by a body of evidence that highlights the benefits of this system over conventional intelligent agents acting in decision support. The proposed model fills a gap within the field of Information Systems for supporting systems that handle uncertainty and ambiguity, enabling end users to take large amounts of data in complex or incomplete environments and turn them into manageable choices.
|Date of Award||20 Jul 2023|
|Supervisor||Peter Bednar (Supervisor), Alexander Gegov (Supervisor) & Christine Welch (Supervisor)|