Reliable Offine Policy Evaluation for Individualized Mechanical Ventilation

Individualizing mechanical ventilation treatment regimes remains a challenge in the intensive care unit (ICU). Reinforcement Learning (RL) offers the potential to improve patient outcomes and reduce mortality risk, by optimizing ventilation treatment regimes. We focus on the Offline RL setting, using Offline Policy Evaluation (OPE), specifically...

Safe Reinforcement Learning by Shielding for Autonomous Vehicles

In the past few years, there has been much research in the field of Autonomous Vehicles (AV). If AVs are implemented in our daily lives, this could have many advantages. Before this can happen, safe driver models need to be designed which control the AVs. One technique that is suitable to create these models is Reinforcement Learning (RL). A...

Safe Optimization of Steel Manufacturing with Reinforcement Learning

Steel production is a complex problem, and little has been done to improve it with the usage of Reinforcement Learning techniques. Most studies focus on decomposing it into sub-problems, instead of tacking it as a whole. Research has shown promising results in the area of safe policy improvement on toy problems. These algorithms are not only...

Reward Definitions in Reinforcement Learning for Traffic Light Control

Traffic congestion is a problem of tremendous size that affects many people. Using Reinforcement Learning to find a light control policy can ease traffic congestion and decrease travel time for vehicles. This paper specifically looks at the effect of using different reward functions for training agents. We highlight how the learnabilty of a...