PhD in Phd

About the Project Self-adaptive and autonomous systems are increasingly deployed in dynamic and uncertain environments, where effective decision-making relies on accurate models of how the system interacts with its environment. This PhD project aims to explore 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 focus on enabling more accurate predictions of adaptation impacts and supporting a better-informed, resilient decision-making process.