Machine Learning to enhance AI Planning for Intelligent Transport Systems

AI planning and scheduling methods are fundamental in industrial transport applications, automating key stages in the overall process of assigning tasks and ensuring that plans remain feasible over time.

These methods typically rely on manually-specified knowledge to derive plans, many aspects of which are only known to human planning experts (e.g., impenetrable forest roads, icy terrain, etc). This project aims to enhanced AI planning and scheduling methods with the ability to learn from human planning experts and from experience. The primary class of use-cases for this project is that of autonomous transport domains.