PhD in Engineering

Location: Streatham Campus About the Project This PhD project aims to address challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined to continuously learn, adapt, and refine world models in self-adaptive and autonomous systems. The research will investigate how AI-based methods can support the evolution and updating of transition and observation models to reflect real-time changes in environmental conditions. Expected Contributions include a novel framework combining evolutionary algorithms and reinforcement learning for adaptive world model learning, methods for continuously refining expert-specified models based on observed environmental feedback, and decision-making approaches that integrate updated models to improve adaptation strategies in uncertain conditions.