**Job Description**
This PhD research project focuses on exploring techniques to facilitate experts in the elicitation of priorities for computing systems operating in dynamic and uncertain environments, specifically within the Internet of Things (IoT). The project aims to develop methods for effective decision-making in systems like smart homes, which must continuously evaluate trade-offs under varying environmental conditions and conflicting requirements. A key direction involves utilizing Inverse Reinforcement Learning (IRL), an AI-based technique, to infer reward values from observed system behaviour, thereby supporting experts in the priority elicitation process.
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