3 papers
cs.LG2026
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…
cs.RO2025
ASVSim (AirSim for Surface Vehicles): A High-Fidelity Simulation Framework for Autonomous Surface Vehicle Research
Bavo Lesy, Siemen Herremans, Robin Kerstens +4
The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway transport. These systems can improve o…
cs.LG2024
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…