1 citations · 3 across the 13 of their papers we have counts for
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Post-Hoc Robustness for Model-Based Reinforcement Learning
Siemen Herremans, Ali Anwar, Siegfried Mercelis
To improve the real-world applicability of reinforcement learning (RL), the field of adversarially robust RL studies how to train agents under adversarial environment perturbations…
Evaluating Robustness of Reinforcement Learning Algorithms for Autonomous Shipping
Bavo Lesy, Ali Anwar, Siegfried Mercelis
Recently, there has been growing interest in autonomous shipping due to its potential to improve maritime efficiency and safety. The use of advanced technologies, such as artificia…
Data selection method for assessment of autonomous vehicles
Linh Trinh, Ali Anwar, Siegfried Mercelis
As the popularity of autonomous vehicles has grown, many standards and regulators, such as ISO, NHTSA, and Euro NCAP, require safety validation to ensure a sufficient level of safe…
Robust Model-Based Reinforcement Learning with an Adversarial Auxiliary Model
Siemen Herremans, Ali Anwar, Siegfried Mercelis
Reinforcement learning has demonstrated impressive performance in various challenging problems such as robotics, board games, and classical arcade games. However, its real-world ap…