1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Autonomous Port Navigation With Ranging Sensors Using Model-Based Reinforcement Learning
Siemen Herremans, Ali Anwar, Arne Troch +4
Autonomous shipping has recently gained much interest in the research community. However, little research focuses on inland - and port navigation, even though this is identified by…