Towards Explainable Automation for Air Traffic Control Using Deep Q-learning from Demonstrations and Reward Decomposition

The current ATC system is seen as the most significant limitation to coping with an increased air traffic density. Transitioning towards an ATC system with a high degree of automation is essential to cope with future traffic demand of the airspace. In recent studies, reinforcement learning has shown promising results automating Conflict...

Actor analysis for water resources management: Putting the promise into practice

Water related problems such as floods, droughts, declining groundwater tables or polluted rivers have a major impact on numerous societies throughout the world. Despite these serious problems, policy makers seem to make scant use of the knowledge that is available with water experts. Conversely, water experts face the task of finding out how...