7 citations · 17 across the 16 of their papers we have counts for
7 papers · 1 filter
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…
Safety Aware Autonomous Path Planning Using Model Predictive Reinforcement Learning for Inland Waterways
Astrid Vanneste, Simon Vanneste, Olivier Vasseur +7
In recent years, interest in autonomous shipping in urban waterways has increased significantly due to the trend of keeping cars and trucks out of city centers. Classical approache…
Heterogeneous Federated Learning using Dynamic Model Pruning and Adaptive Gradient
Sixing Yu, Phuong Nguyen, Ali Anwar +1
Federated Learning (FL) has emerged as a new paradigm for training machine learning models distributively without sacrificing data security and privacy. Learning models on edge dev…
Learning to Communicate Using Counterfactual Reasoning
Simon Vanneste, Astrid Vanneste, Kevin Mets +5
Learning to communicate in order to share state information is an active problem in the area of multi-agent reinforcement learning (MARL). The credit assignment problem, the non-st…