2 – Personalised Reinforcement Learning for Mobility Recommendations

Different travellers may have different preferences when choosing how and when to travel. While some may prioritise travel time, others may prefer cheaper, less crowded or more environmentally friendly options. This project investigates whether reinforcement learning can be used to learn personalised mobility recommendations based on individual preferences and feedback. The project will explore how the recommendations change for different traveller preferences and evaluate whether personalised RL can provide better outcomes than a one-size-fits-all recommendation strategy.