Increasing interpretability in XAI: Addressing the design principles for interactive XUIs to increase interpretability in XAI for end-users

Recent advancements in artificial intelligence (AI), particularly in deep learning, have significantly enhanced AI capabilities but have also led to more complex and less interpretable algorithms. This research addresses the challenge of Explainable AI (XAI) by focusing on enhancing the interpretability of AI decisions through the use of...

Outcome novelty in Exploratory Modellingand Analysis: A research into the value of novelty search for exploratory modelling

Novelty search is a state-of-the-art approach focusing on behavioural novelty, rewarding diverging, as opposed to pursuing static objectives. This is relevant for exploratory modelling and analysis, which focuses on exploration of model through open exploration or directed search. Novelty search as an open exploration strategy is being tested...